This document summarizes key points from a lecture on MPEG-1 video and MP3 audio encoding. It discusses JPEG losses from quantization and introduces MPEG hybrid coding. It describes MPEG video encoding steps including I, P, and B frames, motion estimation, quantization, and decoding order. It also summarizes MP3 audio encoding steps involving filter banks, psychoacoustic modeling, bit allocation, and MP3 audio format.
This document discusses various media compression techniques including JPEG for images, MP3 and AAC for audio, and MPEG standards for video. JPEG takes advantage of human insensitivity to high spatial frequencies to compress images. MP3 audio compression utilizes properties of human hearing like insensitivity to quiet frequencies. MPEG video standards like H.261 and MPEG-2 achieve higher compression by exploiting both spatial and temporal redundancy between frames.
The document discusses MPEG audio compression standards. It provides details on MPEG-1 audio layers including:
- MPEG-1 audio layers 1, 2, and 3 have increasing complexity and performance with layers 1 being the simplest and layers 3 providing the best quality.
- All layers use a filterbank and quantization while layer 3 adds an MDCT transform and improved quantization.
- Layers are decoded using frame unpacking, reconstruction, and inverse mapping processes.
- Frames contain header, allocation, and sample data with headers being more error resistant.
This document summarizes MPEG 1 and 2 video compression standards. It explains the need for video compression due to the large data rates of uncompressed video like HDTV. MPEG compression works by predicting frames from previous frames using motion compensation and coding the residual errors. It uses I, P, and B frames along with other techniques like chroma subsampling to achieve high compression ratios like 83:1 while maintaining quality. MPEG-2 improved upon MPEG-1 by supporting higher resolutions and bitrates needed for digital television.
The document summarizes MPEG video compression standards. It discusses how MPEG was established in 1988 to create standards for coded representation of moving pictures. It describes the different MPEG phases including MPEG-1 used for VCDs, MPEG-2 for DVDs, and MPEG-4 and MPEG-7. It then provides details on MPEG-1 video compression including chrominance subsampling, discrete cosine transform, quantization, entropy coding, and temporal compression using I, P, and B frames and motion vectors.
Digital data compression reduces transmission bandwidth requirements by removing redundant data. There are two types: lossy compression which permanently removes some data, and lossless compression which does not. Common lossy compression standards are JPEG for images and MP3 for audio, while ZIP files use lossless compression. The limits of lossy compression are determined by information theory concepts like source entropy.
Introduction to Video Compression Techniques - Anurag JainVideoguy
The document provides an overview of video compression techniques and standards. It discusses the motivation for video compression to reduce data sizes for storage and transmission. It then reviews several key video compression standards including H.261, H.263, MPEG-1, MPEG-2, MPEG-4, H.264 and others. For each standard, it summarizes the goals, features, applications and technical details like motion compensation methods, block sizes, and bitrate ranges.
The document discusses video compression basics and MPEG-2 video compression. It explains that video frames contain redundant spatial and temporal data that can be compressed. MPEG-2 uses three frame types (I, P, B frames) and compresses frames using intra-frame and inter-frame encoding techniques like DCT, quantization, and entropy encoding to remove redundancy. The encoding process transforms raw video frames to compressed bitstreams for efficient storage and transmission.
This document provides an overview of MPEG-1 audio compression. It describes the key components of the MPEG-1 audio encoder including the polyphase filter bank that transforms audio into frequency subbands, the psychoacoustic model that determines inaudible parts of the signal, and the coding and bit allocation process that assigns bits to subbands. The overview concludes by noting that MPEG-1 audio provides high compression while retaining quality and paved the way for future audio compression standards.
This document discusses various media compression techniques including JPEG for images, MP3 and AAC for audio, and MPEG standards for video. JPEG takes advantage of human insensitivity to high spatial frequencies to compress images. MP3 audio compression utilizes properties of human hearing like insensitivity to quiet frequencies. MPEG video standards like H.261 and MPEG-2 achieve higher compression by exploiting both spatial and temporal redundancy between frames.
The document discusses MPEG audio compression standards. It provides details on MPEG-1 audio layers including:
- MPEG-1 audio layers 1, 2, and 3 have increasing complexity and performance with layers 1 being the simplest and layers 3 providing the best quality.
- All layers use a filterbank and quantization while layer 3 adds an MDCT transform and improved quantization.
- Layers are decoded using frame unpacking, reconstruction, and inverse mapping processes.
- Frames contain header, allocation, and sample data with headers being more error resistant.
This document summarizes MPEG 1 and 2 video compression standards. It explains the need for video compression due to the large data rates of uncompressed video like HDTV. MPEG compression works by predicting frames from previous frames using motion compensation and coding the residual errors. It uses I, P, and B frames along with other techniques like chroma subsampling to achieve high compression ratios like 83:1 while maintaining quality. MPEG-2 improved upon MPEG-1 by supporting higher resolutions and bitrates needed for digital television.
The document summarizes MPEG video compression standards. It discusses how MPEG was established in 1988 to create standards for coded representation of moving pictures. It describes the different MPEG phases including MPEG-1 used for VCDs, MPEG-2 for DVDs, and MPEG-4 and MPEG-7. It then provides details on MPEG-1 video compression including chrominance subsampling, discrete cosine transform, quantization, entropy coding, and temporal compression using I, P, and B frames and motion vectors.
Digital data compression reduces transmission bandwidth requirements by removing redundant data. There are two types: lossy compression which permanently removes some data, and lossless compression which does not. Common lossy compression standards are JPEG for images and MP3 for audio, while ZIP files use lossless compression. The limits of lossy compression are determined by information theory concepts like source entropy.
Introduction to Video Compression Techniques - Anurag JainVideoguy
The document provides an overview of video compression techniques and standards. It discusses the motivation for video compression to reduce data sizes for storage and transmission. It then reviews several key video compression standards including H.261, H.263, MPEG-1, MPEG-2, MPEG-4, H.264 and others. For each standard, it summarizes the goals, features, applications and technical details like motion compensation methods, block sizes, and bitrate ranges.
The document discusses video compression basics and MPEG-2 video compression. It explains that video frames contain redundant spatial and temporal data that can be compressed. MPEG-2 uses three frame types (I, P, B frames) and compresses frames using intra-frame and inter-frame encoding techniques like DCT, quantization, and entropy encoding to remove redundancy. The encoding process transforms raw video frames to compressed bitstreams for efficient storage and transmission.
This document provides an overview of MPEG-1 audio compression. It describes the key components of the MPEG-1 audio encoder including the polyphase filter bank that transforms audio into frequency subbands, the psychoacoustic model that determines inaudible parts of the signal, and the coding and bit allocation process that assigns bits to subbands. The overview concludes by noting that MPEG-1 audio provides high compression while retaining quality and paved the way for future audio compression standards.
This document discusses multimedia concepts including audio encoding, video encoding, and digital formats. It provides information on how audio is converted to digital form through sampling and quantization. Key video encoding concepts covered include luminance, chrominance, resolution, and frame rate. Common audio formats like WAV, AIFF, and video formats like MPEG, AVI are also summarized. The document concludes that a lack of standardization across formats has made building multimedia systems more challenging.
This document discusses various topics related to data compression including compression techniques, audio compression, video compression, and standards like MPEG and JPEG. It covers lossless versus lossy compression, explaining that lossy compression can achieve much higher levels of compression but results in some loss of quality, while lossless compression maintains the original quality. The advantages of data compression include reducing file sizes, saving storage space and bandwidth.
The document introduces JPEG and MPEG standards for image and video compression. JPEG uses DCT, quantization and entropy coding on 8x8 pixel blocks to remove spatial redundancy in images. MPEG builds on JPEG and additionally removes temporal redundancy between video frames using motion compensation in interframe coding of P and B frames. MPEG-1 was designed for video at 1.5Mbps while MPEG-2 supports digital TV and DVD with rates over 4Mbps. Later MPEG standards provide more capabilities for multimedia delivery and interaction.
This is the subject slides for the module MMS2401 - Multimedia System and Communication taught in Shepherd College of Media Technology, Affiliated with Purbanchal University.
I made this presentation in order to convince Web3D and Khronos folks that community and industry need one single standard for 3D graphics compression. It contains a list of MPEG-4 tools for graphics compression that are royalty free and for which open source software implementation exist. A JavaScript implementation of decoder and WebGL complaient MPEG-4 player is also introduced.
The document discusses MPEG-2 video compression. It explains that MPEG-2 builds on MPEG-1 by providing backward compatibility and exploiting both intraframe and interframe redundancies to achieve high compression ratios. It describes how video frames are organized into Groups of Pictures (GOPs) containing I, P, and B frames. The compression steps of discrete cosine transform, weighting, re-quantization, entropy coding, and run length coding are explained. It also discusses how motion compensation of P and B frames further reduces file sizes by only encoding differences between frames.
The document summarizes key video coding standards including H.261, MPEG-1, MPEG-2, H.263, MPEG-4, and H.264. It describes their applications, coding tools, profiles, and roles in important technologies. H.261 was the earliest standard for videoconferencing over ISDN. MPEG-1 enabled video on CDs. MPEG-2 allowed digital TV and DVD. Later standards added features for improved compression and functionality at lower bitrates.
The document discusses audio compression techniques. It begins with an introduction to pulse code modulation (PCM) and then describes μ-law and A-law compression standards which compress audio using companding algorithms. It also covers differential PCM and adaptive differential PCM (ADPCM) techniques. The document then discusses the MPEG audio compression standard, including its encoder architecture, three layer standards (Layers I, II, III), and applications. It concludes with a comparison of various MPEG audio compression standards and references.
This document provides an overview of audio compression techniques. It discusses pulse code modulation (PCM) and its components of sampling, quantizing, and encoding. It also covers μ-law and A-law compression standards. Differential PCM and adaptive differential PCM are introduced as improved compression methods. The document then describes MPEG audio compression, including its encoder architecture, algorithm using filter banks and psychoacoustic modeling, layers (I, II, III), and applications of each layer. It concludes with a comparison of MPEG audio compression standards and bitrates.
Digital video is, a sequence of images, called frames, displayed at a certain frame rate (so many frames per second, or fps) to create the illusion of animation.
An overview Survey on Various Video compressions and its importanceINFOGAIN PUBLICATION
With the rise of digital computing and visual data processing, the need for storage and transmission of video data became prevalent. Storage and transmission of uncompressed raw visual data is not a good practice, because it requires a large storage space and great bandwidth. Video compression algorithms can compress this raw visual data or video into smaller files with a little sacrifice on the quality. This paper an overview and comparison of standard efforts on video compression algorithm of: MPEG-1, MPEG-2, MPEG-4, MPEG-7
The document discusses multimedia and multimedia applications. It covers:
1. The differences between multimedia applications and classic applications in terms of delay sensitivity and packet loss tolerance.
2. The main classes of multimedia applications including streaming stored audio/video, streaming live audio/video, and real-time interactive audio/video. It outlines the requirements and constraints of each class.
3. Problems with delivering multimedia over the Internet like limited bandwidth, packet jitter, and packet loss. It describes solutions to these problems including compression techniques, playout buffering, and forward error correction.
4. Common multimedia protocols including RTP for framing/multiplexing/synchronization and RTCP for feedback. It explains how these
The document discusses different types of data compression techniques. It explains that compression reduces the size of data to reduce bandwidth and storage requirements when transmitting or storing audio, video, and images. It describes how compression works by exploiting redundancies in the data as well as properties of human perception. Various compression methods are outlined, including lossless techniques that preserve all information as well as lossy methods for audio and video that can tolerate some loss of information. Specific algorithms discussed include Huffman coding, run-length coding, LZW coding, and arithmetic coding. The document also provides details on JPEG image compression and MPEG video compression standards.
The document discusses different types of data compression techniques. It explains that compression reduces the size of data to reduce bandwidth and storage requirements when transmitting or storing audio, video, and images. It describes how compression works by exploiting redundancies in the data as well as properties of human perception. Various compression methods are outlined, including lossless techniques that preserve all information as well as lossy methods for audio and video that can tolerate some loss of information. Specific algorithms discussed include Huffman coding, run-length coding, LZW coding, and arithmetic coding. The document also provides details on JPEG image compression and MPEG video compression standards.
The document discusses image compression techniques. It outlines the fundamentals of image compression including encoding, decoding, and algorithms like JPEG and JPEG 2000. Image compression aims to reduce data storage and transmission requirements by removing redundant pixel information. It allows for more efficient sharing and storage of images across industries like printing, data storage, telecommunications, satellite imaging, and television.
The document discusses video transcoding for mobile telephony. It motivates the need for video transcoding by describing how mobile users may experience bandwidth reductions during calls, requiring the video bitrate to be lowered. It then provides an overview of video coding standards and how transcoding can convert a compressed video stream to a different format, resolution, frame rate or quality level. Future work is proposed to address video transcoding challenges caused by temporary bandwidth reductions during mobile calls.
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
The papers for publication in The International Journal of Engineering& Science are selected through rigorous peer reviews to ensure originality, timeliness, relevance, and readability.
A presentation covering some basic aspects of digital video data and the compression of video images. The ATSC system architecture is shown using the OSI 7-layer model from data communication theory. Video compression techniques are briefly covered.
This document provides an overview of fundamental concepts in video and multimedia technology. It discusses the differences between analog and digital video, including how analog video uses continuous electric signals while digital video represents images as binary digits. It also covers topics like interlaced vs progressive scanning, component vs composite video signals, common video file formats, and standards for analog TV broadcasting like NTSC, PAL, and SECAM. Key video concepts like frame rate, color resolution, spatial resolution, and image quality that apply to digital video are also defined.
1. The document discusses video compression technology, including digital television formats, video compression standards like MPEG-2 and H.264, video quality metrics, and video coding concepts.
2. Key video coding concepts covered are temporal compression using motion estimation and compensation between frames, spatial compression within frames using DCT transform and quantization, and entropy coding of coefficients.
3. Video compression aims to reduce the data required for transmission by removing spatial and temporal redundancy in video sequences.
Digital Marketing Trends in 2024 | Guide for Staying AheadWask
https://www.wask.co/ebooks/digital-marketing-trends-in-2024
Feeling lost in the digital marketing whirlwind of 2024? Technology is changing, consumer habits are evolving, and staying ahead of the curve feels like a never-ending pursuit. This e-book is your compass. Dive into actionable insights to handle the complexities of modern marketing. From hyper-personalization to the power of user-generated content, learn how to build long-term relationships with your audience and unlock the secrets to success in the ever-shifting digital landscape.
This document discusses multimedia concepts including audio encoding, video encoding, and digital formats. It provides information on how audio is converted to digital form through sampling and quantization. Key video encoding concepts covered include luminance, chrominance, resolution, and frame rate. Common audio formats like WAV, AIFF, and video formats like MPEG, AVI are also summarized. The document concludes that a lack of standardization across formats has made building multimedia systems more challenging.
This document discusses various topics related to data compression including compression techniques, audio compression, video compression, and standards like MPEG and JPEG. It covers lossless versus lossy compression, explaining that lossy compression can achieve much higher levels of compression but results in some loss of quality, while lossless compression maintains the original quality. The advantages of data compression include reducing file sizes, saving storage space and bandwidth.
The document introduces JPEG and MPEG standards for image and video compression. JPEG uses DCT, quantization and entropy coding on 8x8 pixel blocks to remove spatial redundancy in images. MPEG builds on JPEG and additionally removes temporal redundancy between video frames using motion compensation in interframe coding of P and B frames. MPEG-1 was designed for video at 1.5Mbps while MPEG-2 supports digital TV and DVD with rates over 4Mbps. Later MPEG standards provide more capabilities for multimedia delivery and interaction.
This is the subject slides for the module MMS2401 - Multimedia System and Communication taught in Shepherd College of Media Technology, Affiliated with Purbanchal University.
I made this presentation in order to convince Web3D and Khronos folks that community and industry need one single standard for 3D graphics compression. It contains a list of MPEG-4 tools for graphics compression that are royalty free and for which open source software implementation exist. A JavaScript implementation of decoder and WebGL complaient MPEG-4 player is also introduced.
The document discusses MPEG-2 video compression. It explains that MPEG-2 builds on MPEG-1 by providing backward compatibility and exploiting both intraframe and interframe redundancies to achieve high compression ratios. It describes how video frames are organized into Groups of Pictures (GOPs) containing I, P, and B frames. The compression steps of discrete cosine transform, weighting, re-quantization, entropy coding, and run length coding are explained. It also discusses how motion compensation of P and B frames further reduces file sizes by only encoding differences between frames.
The document summarizes key video coding standards including H.261, MPEG-1, MPEG-2, H.263, MPEG-4, and H.264. It describes their applications, coding tools, profiles, and roles in important technologies. H.261 was the earliest standard for videoconferencing over ISDN. MPEG-1 enabled video on CDs. MPEG-2 allowed digital TV and DVD. Later standards added features for improved compression and functionality at lower bitrates.
The document discusses audio compression techniques. It begins with an introduction to pulse code modulation (PCM) and then describes μ-law and A-law compression standards which compress audio using companding algorithms. It also covers differential PCM and adaptive differential PCM (ADPCM) techniques. The document then discusses the MPEG audio compression standard, including its encoder architecture, three layer standards (Layers I, II, III), and applications. It concludes with a comparison of various MPEG audio compression standards and references.
This document provides an overview of audio compression techniques. It discusses pulse code modulation (PCM) and its components of sampling, quantizing, and encoding. It also covers μ-law and A-law compression standards. Differential PCM and adaptive differential PCM are introduced as improved compression methods. The document then describes MPEG audio compression, including its encoder architecture, algorithm using filter banks and psychoacoustic modeling, layers (I, II, III), and applications of each layer. It concludes with a comparison of MPEG audio compression standards and bitrates.
Digital video is, a sequence of images, called frames, displayed at a certain frame rate (so many frames per second, or fps) to create the illusion of animation.
An overview Survey on Various Video compressions and its importanceINFOGAIN PUBLICATION
With the rise of digital computing and visual data processing, the need for storage and transmission of video data became prevalent. Storage and transmission of uncompressed raw visual data is not a good practice, because it requires a large storage space and great bandwidth. Video compression algorithms can compress this raw visual data or video into smaller files with a little sacrifice on the quality. This paper an overview and comparison of standard efforts on video compression algorithm of: MPEG-1, MPEG-2, MPEG-4, MPEG-7
The document discusses multimedia and multimedia applications. It covers:
1. The differences between multimedia applications and classic applications in terms of delay sensitivity and packet loss tolerance.
2. The main classes of multimedia applications including streaming stored audio/video, streaming live audio/video, and real-time interactive audio/video. It outlines the requirements and constraints of each class.
3. Problems with delivering multimedia over the Internet like limited bandwidth, packet jitter, and packet loss. It describes solutions to these problems including compression techniques, playout buffering, and forward error correction.
4. Common multimedia protocols including RTP for framing/multiplexing/synchronization and RTCP for feedback. It explains how these
The document discusses different types of data compression techniques. It explains that compression reduces the size of data to reduce bandwidth and storage requirements when transmitting or storing audio, video, and images. It describes how compression works by exploiting redundancies in the data as well as properties of human perception. Various compression methods are outlined, including lossless techniques that preserve all information as well as lossy methods for audio and video that can tolerate some loss of information. Specific algorithms discussed include Huffman coding, run-length coding, LZW coding, and arithmetic coding. The document also provides details on JPEG image compression and MPEG video compression standards.
The document discusses different types of data compression techniques. It explains that compression reduces the size of data to reduce bandwidth and storage requirements when transmitting or storing audio, video, and images. It describes how compression works by exploiting redundancies in the data as well as properties of human perception. Various compression methods are outlined, including lossless techniques that preserve all information as well as lossy methods for audio and video that can tolerate some loss of information. Specific algorithms discussed include Huffman coding, run-length coding, LZW coding, and arithmetic coding. The document also provides details on JPEG image compression and MPEG video compression standards.
The document discusses image compression techniques. It outlines the fundamentals of image compression including encoding, decoding, and algorithms like JPEG and JPEG 2000. Image compression aims to reduce data storage and transmission requirements by removing redundant pixel information. It allows for more efficient sharing and storage of images across industries like printing, data storage, telecommunications, satellite imaging, and television.
The document discusses video transcoding for mobile telephony. It motivates the need for video transcoding by describing how mobile users may experience bandwidth reductions during calls, requiring the video bitrate to be lowered. It then provides an overview of video coding standards and how transcoding can convert a compressed video stream to a different format, resolution, frame rate or quality level. Future work is proposed to address video transcoding challenges caused by temporary bandwidth reductions during mobile calls.
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
The papers for publication in The International Journal of Engineering& Science are selected through rigorous peer reviews to ensure originality, timeliness, relevance, and readability.
A presentation covering some basic aspects of digital video data and the compression of video images. The ATSC system architecture is shown using the OSI 7-layer model from data communication theory. Video compression techniques are briefly covered.
This document provides an overview of fundamental concepts in video and multimedia technology. It discusses the differences between analog and digital video, including how analog video uses continuous electric signals while digital video represents images as binary digits. It also covers topics like interlaced vs progressive scanning, component vs composite video signals, common video file formats, and standards for analog TV broadcasting like NTSC, PAL, and SECAM. Key video concepts like frame rate, color resolution, spatial resolution, and image quality that apply to digital video are also defined.
1. The document discusses video compression technology, including digital television formats, video compression standards like MPEG-2 and H.264, video quality metrics, and video coding concepts.
2. Key video coding concepts covered are temporal compression using motion estimation and compensation between frames, spatial compression within frames using DCT transform and quantization, and entropy coding of coefficients.
3. Video compression aims to reduce the data required for transmission by removing spatial and temporal redundancy in video sequences.
Digital Marketing Trends in 2024 | Guide for Staying AheadWask
https://www.wask.co/ebooks/digital-marketing-trends-in-2024
Feeling lost in the digital marketing whirlwind of 2024? Technology is changing, consumer habits are evolving, and staying ahead of the curve feels like a never-ending pursuit. This e-book is your compass. Dive into actionable insights to handle the complexities of modern marketing. From hyper-personalization to the power of user-generated content, learn how to build long-term relationships with your audience and unlock the secrets to success in the ever-shifting digital landscape.
Main news related to the CCS TSI 2023 (2023/1695)Jakub Marek
An English 🇬🇧 translation of a presentation to the speech I gave about the main changes brought by CCS TSI 2023 at the biggest Czech conference on Communications and signalling systems on Railways, which was held in Clarion Hotel Olomouc from 7th to 9th November 2023 (konferenceszt.cz). Attended by around 500 participants and 200 on-line followers.
The original Czech 🇨🇿 version of the presentation can be found here: https://www.slideshare.net/slideshow/hlavni-novinky-souvisejici-s-ccs-tsi-2023-2023-1695/269688092 .
The videorecording (in Czech) from the presentation is available here: https://youtu.be/WzjJWm4IyPk?si=SImb06tuXGb30BEH .
Monitoring and Managing Anomaly Detection on OpenShift.pdfTosin Akinosho
Monitoring and Managing Anomaly Detection on OpenShift
Overview
Dive into the world of anomaly detection on edge devices with our comprehensive hands-on tutorial. This SlideShare presentation will guide you through the entire process, from data collection and model training to edge deployment and real-time monitoring. Perfect for those looking to implement robust anomaly detection systems on resource-constrained IoT/edge devices.
Key Topics Covered
1. Introduction to Anomaly Detection
- Understand the fundamentals of anomaly detection and its importance in identifying unusual behavior or failures in systems.
2. Understanding Edge (IoT)
- Learn about edge computing and IoT, and how they enable real-time data processing and decision-making at the source.
3. What is ArgoCD?
- Discover ArgoCD, a declarative, GitOps continuous delivery tool for Kubernetes, and its role in deploying applications on edge devices.
4. Deployment Using ArgoCD for Edge Devices
- Step-by-step guide on deploying anomaly detection models on edge devices using ArgoCD.
5. Introduction to Apache Kafka and S3
- Explore Apache Kafka for real-time data streaming and Amazon S3 for scalable storage solutions.
6. Viewing Kafka Messages in the Data Lake
- Learn how to view and analyze Kafka messages stored in a data lake for better insights.
7. What is Prometheus?
- Get to know Prometheus, an open-source monitoring and alerting toolkit, and its application in monitoring edge devices.
8. Monitoring Application Metrics with Prometheus
- Detailed instructions on setting up Prometheus to monitor the performance and health of your anomaly detection system.
9. What is Camel K?
- Introduction to Camel K, a lightweight integration framework built on Apache Camel, designed for Kubernetes.
10. Configuring Camel K Integrations for Data Pipelines
- Learn how to configure Camel K for seamless data pipeline integrations in your anomaly detection workflow.
11. What is a Jupyter Notebook?
- Overview of Jupyter Notebooks, an open-source web application for creating and sharing documents with live code, equations, visualizations, and narrative text.
12. Jupyter Notebooks with Code Examples
- Hands-on examples and code snippets in Jupyter Notebooks to help you implement and test anomaly detection models.
Ocean lotus Threat actors project by John Sitima 2024 (1).pptxSitimaJohn
Ocean Lotus cyber threat actors represent a sophisticated, persistent, and politically motivated group that poses a significant risk to organizations and individuals in the Southeast Asian region. Their continuous evolution and adaptability underscore the need for robust cybersecurity measures and international cooperation to identify and mitigate the threats posed by such advanced persistent threat groups.
Salesforce Integration for Bonterra Impact Management (fka Social Solutions A...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on integration of Salesforce with Bonterra Impact Management.
Interested in deploying an integration with Salesforce for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
GraphRAG for Life Science to increase LLM accuracyTomaz Bratanic
GraphRAG for life science domain, where you retriever information from biomedical knowledge graphs using LLMs to increase the accuracy and performance of generated answers
Ivanti’s Patch Tuesday breakdown goes beyond patching your applications and brings you the intelligence and guidance needed to prioritize where to focus your attention first. Catch early analysis on our Ivanti blog, then join industry expert Chris Goettl for the Patch Tuesday Webinar Event. There we’ll do a deep dive into each of the bulletins and give guidance on the risks associated with the newly-identified vulnerabilities.
Driving Business Innovation: Latest Generative AI Advancements & Success StorySafe Software
Are you ready to revolutionize how you handle data? Join us for a webinar where we’ll bring you up to speed with the latest advancements in Generative AI technology and discover how leveraging FME with tools from giants like Google Gemini, Amazon, and Microsoft OpenAI can supercharge your workflow efficiency.
During the hour, we’ll take you through:
Guest Speaker Segment with Hannah Barrington: Dive into the world of dynamic real estate marketing with Hannah, the Marketing Manager at Workspace Group. Hear firsthand how their team generates engaging descriptions for thousands of office units by integrating diverse data sources—from PDF floorplans to web pages—using FME transformers, like OpenAIVisionConnector and AnthropicVisionConnector. This use case will show you how GenAI can streamline content creation for marketing across the board.
Ollama Use Case: Learn how Scenario Specialist Dmitri Bagh has utilized Ollama within FME to input data, create custom models, and enhance security protocols. This segment will include demos to illustrate the full capabilities of FME in AI-driven processes.
Custom AI Models: Discover how to leverage FME to build personalized AI models using your data. Whether it’s populating a model with local data for added security or integrating public AI tools, find out how FME facilitates a versatile and secure approach to AI.
We’ll wrap up with a live Q&A session where you can engage with our experts on your specific use cases, and learn more about optimizing your data workflows with AI.
This webinar is ideal for professionals seeking to harness the power of AI within their data management systems while ensuring high levels of customization and security. Whether you're a novice or an expert, gain actionable insights and strategies to elevate your data processes. Join us to see how FME and AI can revolutionize how you work with data!
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAUpanagenda
Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-und-domino-lizenzkostenreduzierung-in-der-welt-von-dlau/
DLAU und die Lizenzen nach dem CCB- und CCX-Modell sind für viele in der HCL-Community seit letztem Jahr ein heißes Thema. Als Notes- oder Domino-Kunde haben Sie vielleicht mit unerwartet hohen Benutzerzahlen und Lizenzgebühren zu kämpfen. Sie fragen sich vielleicht, wie diese neue Art der Lizenzierung funktioniert und welchen Nutzen sie Ihnen bringt. Vor allem wollen Sie sicherlich Ihr Budget einhalten und Kosten sparen, wo immer möglich. Das verstehen wir und wir möchten Ihnen dabei helfen!
Wir erklären Ihnen, wie Sie häufige Konfigurationsprobleme lösen können, die dazu führen können, dass mehr Benutzer gezählt werden als nötig, und wie Sie überflüssige oder ungenutzte Konten identifizieren und entfernen können, um Geld zu sparen. Es gibt auch einige Ansätze, die zu unnötigen Ausgaben führen können, z. B. wenn ein Personendokument anstelle eines Mail-Ins für geteilte Mailboxen verwendet wird. Wir zeigen Ihnen solche Fälle und deren Lösungen. Und natürlich erklären wir Ihnen das neue Lizenzmodell.
Nehmen Sie an diesem Webinar teil, bei dem HCL-Ambassador Marc Thomas und Gastredner Franz Walder Ihnen diese neue Welt näherbringen. Es vermittelt Ihnen die Tools und das Know-how, um den Überblick zu bewahren. Sie werden in der Lage sein, Ihre Kosten durch eine optimierte Domino-Konfiguration zu reduzieren und auch in Zukunft gering zu halten.
Diese Themen werden behandelt
- Reduzierung der Lizenzkosten durch Auffinden und Beheben von Fehlkonfigurationen und überflüssigen Konten
- Wie funktionieren CCB- und CCX-Lizenzen wirklich?
- Verstehen des DLAU-Tools und wie man es am besten nutzt
- Tipps für häufige Problembereiche, wie z. B. Team-Postfächer, Funktions-/Testbenutzer usw.
- Praxisbeispiele und Best Practices zum sofortigen Umsetzen
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lect10-mpeg1.ppt
1. CS 414 - Spring 2010
CS 414 – Multimedia Systems Design
Lecture 10 – MPEG-1 Video
and MP3 Audio) (Part 5)
Klara Nahrstedt
Spring 2010
2. CS 414 - Spring 2010
Administrative
MP2 posted on February 9 and deadline
will be March 1
MP2 demos – Monday, March 1, 5-7pm,
0216 SC
Please, start early
We will have a discussion section next
week for MP2
3. Outline
Few Comments about losses that occur in
JPEG (and similar in MPEG later on)
MPEG-1 Hybrid Coding
MP3 Audio Encoding
Reading:
Required: Media Coding Book, Section 7.7.1-7.7.4 and lectures
Recommended Paper on MP3: Davis Pan, “A Tutorial on MPEG/Audio
Compression”, IEEE Multimedia, pp. 6-74, 1995
Recommended books on JPEG/ MPEG Audio/Video Fundamentals:
Haskell, Puri, Netravali, “Digital Video: An Introduction to MPEG-2”,
Chapman and Hall, 1996
Pennebaker, Mitchel, “JPEG: Still Image Data Compression Standard,
VNR Publisher, 1993
CS 414 - Spring 2010
4. Comment on JPEG Losses
Losses in JPEG compression occur during the
quantization because S(u,v)’ = Round(S(u,v)/Q(u,v)).
1. Image Preparation =>
2. DCT Transform S(u,v) = DCT(S(x,y)) =>
3. Quantization with S(u,v)’ = Round(S(u,v)/Q(u,v) =>
4. Entropy Encoding =>
5. Transmission of compressed Image =>
6. Entropy Decoding =>
7. De-quantization S(u,v)’’ = S(u,v)’*Q(u,v) Compression Loss
since S(u,v)” ≠ S(u,v) =>
8. Apply Inverse DCT =>
9. Display Image CS 414 - Spring 2010
5. Motion Picture Expert Group
(MPEG)
General Information about MPEG
Began in 1988; Part of Same ISO as JPEG
MPEG-1/Video
MPEG/Audio – MP3
MPEG-2
MPEG-4
MPEG-7
MPEG-21 CS 414 - Spring 2010
6. MPEG General Information
Goal: data compression 1.5 Mbps
MPEG defines video, audio coding and
system data streams with synchronization
MPEG information
Aspect ratios: 1:1 (CRT), 4:3 (NTSC), 16:9
(HDTV)
Refresh frequencies: 23.975, 24, 25, 29.97,
50, 59.94, 60 Hz
CS 414 - Spring 2010
7. MPEG Image Preparation
(Resolution and Dimension)
MPEG defines exactly format
Three components: Luminance and two chrominance
components (2:1:1)
Resolution of luminance comp:X1 ≤ 768; Y1 ≤ 576
pixels
Pixel precision is 8 bits for each component
Example of Video format: 352x240 pixels, 30
fps; chrominance components: 176x120 pixels
CS 414 - Spring 2010
8. MPEG Image Preparation -
Blocks
Each image is divided into macro-blocks
Macro-block : 16x16 pixels for luminance;
8x8 for each chrominance component
Macro-blocks are useful for Motion
Estimation
No MCUs which implies sequential non-
interleaving order of pixels values
CS 414 - Spring 2010
9. MPEG Video Processing
Intra frames (same as JPEG)
typically about 12 frames between I frames
Predictive frames
encode from previous I or P reference frame
Bi-directional frames
encode from previous and future I or P frames
CS 414 - Spring 2010
I P I
P P
B B B B B B B B
10. Selecting I, P, or B Frames
Heuristics
change of scenes should generate I frame
limit B and P frames between I frames
B frames are computationally intense
Type Size Compress
I 18K 7:1
P 6K 20:1
B 2.5K 50:1
Avg 4.8K 27:1
CS 414 - Spring 2010
11. MPEG Video I-Frames
CS 414 - Spring 2010
Intra-coded images
I-frames – points of
random access in
MPEG stream
I-frames use 8x8
blocks defined within
Macro-block
No quantization
table for all DCT
coefficients, only
quantization factor
12. MPEG Video P-Frames
CS 414 - Spring 2010
Predictive coded frames
require information of
previous I frame and or
previous P frame for
encoding/decoding
For Temporary Redundancy
we determine last P or I frame
that is most similar to the
block under consideration
Motion Estimation Method
13. Motion Computation for P
Frames
Predictive search
Look for match window within a given
search window
Match window – macro-block
Search window – arbitrary window size
depending how far away are we willing to look
Displacement of two match windows is
expressed by motion vector
CS 414 - Spring 2010
14. Matching Methods
SSD metric
SAD metric
Minimum error represents best match
must be below a specified threshold
error and perceptual similarity not always correlated
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SSD
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SAD
CS 414 - Spring 2010
15. CS 414 - Spring 2010
Example of Finding Minimal SSD
16. CS 414 - Spring 2010
Example of Comparing Minimal SSD and
SAD
17. Syntax of P Frame
CS 414 - Spring 2010
Addr: address the syntax of P frame
Type: INTRA block is specified if no good match was found
Quant: quantization value per macro-block (vary quantization to
fine-tune compression)
Motion Vector: a 2D vector used for motion compensation provides
offset from coordinate position in target image to
coordinates in reference image
CBP(Coded Block Pattern): bit mask indicates which blocks are
present
18. MPEG Video B Frames
CS 414 - Spring 2010
Bi-directionally Predictive-coded frames
19. MPEG Video Decoding
CS 414 - Spring 2010
I1 P1 I2
P2 P3
B1 B2 B3 B4 B5 B6 B7 B8
B2
I1 P1 I2
P2 P3
B1 B3 B4 B5 B6 B7 B8
Display Order
Decoding Order
20. MPEG Video Quantization
AC coefficients of B/P frames are usually
large values, I frames have smaller values
Adjust quantization
If data rate increases over threshold, then
quantization enlarges step size (increase
quantization factor Q)
If data rate decreases below threshold,
then quantization decreases Q
CS 414 - Spring 2010
24. MPEG Audio Filter Bank
Filter bank divides input into multiple sub-bands
(32 equal frequency sub-bands)
Sub-band i defined
- filter output sample for sub-band
i at time t, C[n] – one of 512 coefficients, x[n] –
audio input sample from 512 sample buffer
CS 414 - Spring 2010
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25. MPEG Audio Psycho-acoustic
Model
MPEG audio compresses by removing
acoustically irrelevant parts of audio signals
Takes advantage of human auditory systems
inability to hear quantization noise under
auditory masking
Auditory masking: occurs when ever the
presence of a strong audio signal makes a
temporal or spectral neighborhood of weaker
audio signals imperceptible.
CS 414 - Spring 2010
26. CS 414 - Spring 2010
MPEG/audio divides audio signal into frequency sub-bands that approximate critical
bands. Then we quantize each sub-band according to the audibility of quantization
noise within the band
27. MPEG Audio Bit Allocation
This process determines number of code bits allocated to
each sub-band based on information from the psycho-
acoustic model
Algorithm:
1. Compute mask-to-noise ratio: MNR=SNR-SMR
Standard provides tables that give estimates for SNR resulting
from quantizing to a given number of quantizer levels
2. Get MNR for each sub-band
3. Search for sub-band with the lowest MNR
4. Allocate code bits to this sub-band.
If sub-band gets allocated more code bits than appropriate, look
up new estimate of SNR and repeat step 1
CS 414 - Spring 2010
28. MP3 Audio Format
CS 414 - Spring 2010
Source: http://wiki.hydrogenaudio.org/images/e/ee/Mp3filestructure.jpg
29. MPEG Audio Comments
Precision of 16 bits per sample is needed to get
good SNR ratio
Noise we are getting is quantization noise from
the digitization process
For each added bit, we get 6dB better SNR ratio
Masking effect means that we can raise the
noise floor around a strong sound because the
noise will be masked away
Raising noise floor is the same as using less bits
and using less bits is the same as compression
CS 414 - Spring 2010
30. Conclusion
MPEG system data stream
Interchange format for audio and video streams
Interleave audio and video packets; insert time stamps into each “frame”
of data
Synchronization
SRC – system clock reference; DTS – decoding time stamp; PTS –
presentation time stamp
During encoding
Insert SCR values into system stream
Stamp each frame with PTS and DTS
Use encode time to approximate decode time
During decoding
Initialize local decoder clock with start values
Compare PTS to the value of local clock
Periodically synchronize local clock to SCR
CS 414 - Spring 2010