Color grading is a post-processing effect that allows manipulation of colors in real-time rendered images to change the mood or atmosphere. It works by sampling values from a 3D texture containing projected color values to grade input pixel colors. Implementing color grading requires creating a volume texture for the projected colors and using it in a pixel shader to sample graded output colors based on input pixel values.
GTC 2014 - DirectX 11 Rendering and NVIDIA GameWorks in Batman: Arkham OriginsColin Barré-Brisebois
An extended version from the GDC14 "Deformable Snow Rendering in Batman: Arkham Origins" talk. This talk focuses on several DirectX 11 features developed/integrated in collaboration with NVIDIA. Tessellation and how the integration NVIDIA GameWorks with features such as physically-based particles with PhysX, particle fields with Turbulence, HBAO+, and bokeh DOF is also presented. Other improvements are also showcased: Reoriented Normal Mapping and chroma subsampling pipeline improvements.
GTC 2014 - DirectX 11 Rendering and NVIDIA GameWorks in Batman: Arkham OriginsColin Barré-Brisebois
An extended version from the GDC14 "Deformable Snow Rendering in Batman: Arkham Origins" talk. This talk focuses on several DirectX 11 features developed/integrated in collaboration with NVIDIA. Tessellation and how the integration NVIDIA GameWorks with features such as physically-based particles with PhysX, particle fields with Turbulence, HBAO+, and bokeh DOF is also presented. Other improvements are also showcased: Reoriented Normal Mapping and chroma subsampling pipeline improvements.
COLOUR IMAGE ENHANCEMENT BASED ON HISTOGRAM EQUALIZATIONecij
Histogram equalization is a nonlinear technique for adjusting the contrast of an image using its
histogram. It increases the brightness of a gray scale image which is different from the mean brightness of
the original image. There are various types of Histogram equalization techniques like Histogram
Equalization, Contrast Limited Adaptive Histogram Equalization, Brightness Preserving Bi Histogram
Equalization, Dualistic Sub Image Histogram Equalization, Minimum Mean Brightness Error Bi
Histogram Equalization, Recursive Mean Separate Histogram Equalization and Recursive Sub Image
Histogram Equalization. In this paper, the histogram equalization approach of gray-level images is
extended for colour images. The acquired image is converted into HSV (Hue, Saturation, Value). The
image is then decomposed into two parts by using exposure threshold and then equalized them
independently Over enhancement is also controlled in this method by using clipping threshold. For
measuring the performance of the enhanced image, entropy and contrast are calculated.
IMAGE ENHANCEMENT IN CASE OF UNEVEN ILLUMINATION USING VARIABLE THRESHOLDING ...ijsrd.com
Uneven illumination always affects the visual quality images which results in poor understanding about the content of the images. There is no accepted universal image enhancement algorithm or specific criteria which can fulfill user needs. The processed image may be very different with the original image in the visual effects, but it also may be similar to the original image [1]. It will be a developing tradition to integrate the advantage of various algorithms to practical application to image enhancements [2]. Zhang et al. [3] presents an adaptive image contrast enhancement method. The proposed method is based on a local gamma correction piloted by histogram analysis. In this paper , to avoid uneven Illuminance image is divided into different segments . It works locally to decrease contrast as if we perform enhancement techniques globally on portions which are already bright then this gives poor results. Enhancement techniques are applied only to those dark portions. We need accurate method that not only enhance the image but also preserve the information.
Here in the ppt a detailed description of Image Enhancement Techniques is given which includes topics like Basic Gray level Transformations,Histogram Processing.
Enhancement using Arithmetic/Logic Operations.
image averaging and image averaging methods.
Piecewise-Linear Transformation Functions
Computer Graphics and its applications, Elements of a Graphics, Graphics Systems: Video Display Devices, Raster Scan Systems, Random Scan Systems, Input devices.
: Introduction of Rendering, Raytracing, Antialiasing, Fractals
Image enhancement is the process of adjusting digital images so that the results are more suitable for display or further image analysis. For example, you can remove noise, sharpen, or brighten an image, making it easier to identify key features.
Here are some useful examples and methods of image enhancement:
Filtering with morphological operators, Histogram equalization, Noise removal using a Wiener filter, Linear contrast adjustment, Median filtering, Unsharp mask filtering, Contrast-limited adaptive histogram equalization (CLAHE). Decorrelation stretch
A technical deep dive into the DX11 rendering in Battlefield 3, the first title to use the new Frostbite 2 Engine. Topics covered include DX11 optimization techniques, efficient deferred shading, high-quality rendering and resource streaming for creating large and highly-detailed dynamic environments on modern PCs.
Digital image processing using matlab: basic transformations, filters and ope...thanh nguyen
How to use Matlab to deal with basic image manipulations.
Negative transformation
Log transformation
Power-law transformation
Piecewise-linear transformation
Histogram equalization
Subtraction
Smoothing Linear Filters
Order-Statistics Filters
The Laplacian
The Gradient
COLOUR IMAGE ENHANCEMENT BASED ON HISTOGRAM EQUALIZATIONecij
Histogram equalization is a nonlinear technique for adjusting the contrast of an image using its
histogram. It increases the brightness of a gray scale image which is different from the mean brightness of
the original image. There are various types of Histogram equalization techniques like Histogram
Equalization, Contrast Limited Adaptive Histogram Equalization, Brightness Preserving Bi Histogram
Equalization, Dualistic Sub Image Histogram Equalization, Minimum Mean Brightness Error Bi
Histogram Equalization, Recursive Mean Separate Histogram Equalization and Recursive Sub Image
Histogram Equalization. In this paper, the histogram equalization approach of gray-level images is
extended for colour images. The acquired image is converted into HSV (Hue, Saturation, Value). The
image is then decomposed into two parts by using exposure threshold and then equalized them
independently Over enhancement is also controlled in this method by using clipping threshold. For
measuring the performance of the enhanced image, entropy and contrast are calculated.
IMAGE ENHANCEMENT IN CASE OF UNEVEN ILLUMINATION USING VARIABLE THRESHOLDING ...ijsrd.com
Uneven illumination always affects the visual quality images which results in poor understanding about the content of the images. There is no accepted universal image enhancement algorithm or specific criteria which can fulfill user needs. The processed image may be very different with the original image in the visual effects, but it also may be similar to the original image [1]. It will be a developing tradition to integrate the advantage of various algorithms to practical application to image enhancements [2]. Zhang et al. [3] presents an adaptive image contrast enhancement method. The proposed method is based on a local gamma correction piloted by histogram analysis. In this paper , to avoid uneven Illuminance image is divided into different segments . It works locally to decrease contrast as if we perform enhancement techniques globally on portions which are already bright then this gives poor results. Enhancement techniques are applied only to those dark portions. We need accurate method that not only enhance the image but also preserve the information.
Here in the ppt a detailed description of Image Enhancement Techniques is given which includes topics like Basic Gray level Transformations,Histogram Processing.
Enhancement using Arithmetic/Logic Operations.
image averaging and image averaging methods.
Piecewise-Linear Transformation Functions
Computer Graphics and its applications, Elements of a Graphics, Graphics Systems: Video Display Devices, Raster Scan Systems, Random Scan Systems, Input devices.
: Introduction of Rendering, Raytracing, Antialiasing, Fractals
Image enhancement is the process of adjusting digital images so that the results are more suitable for display or further image analysis. For example, you can remove noise, sharpen, or brighten an image, making it easier to identify key features.
Here are some useful examples and methods of image enhancement:
Filtering with morphological operators, Histogram equalization, Noise removal using a Wiener filter, Linear contrast adjustment, Median filtering, Unsharp mask filtering, Contrast-limited adaptive histogram equalization (CLAHE). Decorrelation stretch
A technical deep dive into the DX11 rendering in Battlefield 3, the first title to use the new Frostbite 2 Engine. Topics covered include DX11 optimization techniques, efficient deferred shading, high-quality rendering and resource streaming for creating large and highly-detailed dynamic environments on modern PCs.
Digital image processing using matlab: basic transformations, filters and ope...thanh nguyen
How to use Matlab to deal with basic image manipulations.
Negative transformation
Log transformation
Power-law transformation
Piecewise-linear transformation
Histogram equalization
Subtraction
Smoothing Linear Filters
Order-Statistics Filters
The Laplacian
The Gradient
Filmic Tonemapping for Real-time Rendering - Siggraph 2010 Color Coursehpduiker
Filmic Tonemapping for Real-time Rendering, a presentation from the Siggraph 2010 Course on Color, on a technique developed from film that became very applicable to games with the addition of support for HDR lighting and rendering in graphics cards.
Volume rendering 3D volume data (medical CT scans) in Unity3D.
Covering the following topics:
- Raymarching
- Maximum Intensity Projection
- Direct Volume Rendering with compositing
- Isosurface rendering
- Transfer functions
- 2D Transfer Functions
- Slice rendering
Source code here: https://github.com/mlavik1/UnityVolumeRendering
IMPORTANCE OF IMAGE ENHANCEMENT TECHNIQUES IN COLOR IMAGE SEGMENTATION: A COM...Dibya Jyoti Bora
Color image segmentation is a very emerging research topic in the area of color image analysis and pattern recognition. Many state-of-the-art algorithms have been developed for this purpose. But, often the segmentation results of these algorithms seem to be suffering from miss-classifications and over-segmentation. The reasons behind these are the degradation of image quality during the acquisition, transmission and color space conversion. So, here arises the need of an efficient image enhancement technique which can remove the redundant pixels or noises from the color image before proceeding for final segmentation. In this paper, an effort has been made to study and analyze different image enhancement techniques and thereby finding out the better one for color image segmentation. Also, this comparative study is done on two well-known color spaces HSV and LAB separately to find out which color space supports segmentation task more efficiently with respect to those enhancement techniques.
Sign Language Recognition Using Image Processing For Mute Peoplepaperpublications3
Abstract: Computer recognition of sign language is an important research problem for enabling communication with mute people. This project introduces an efficient and fast algorithm for identification of the number of fingers opened in a gesture representing an alphabet of the Binary Sign Language.
The system does not require the hand to be perfectly aligned to the camera. The project uses image processing system to identify, especially English alphabetic sign language used by the mute people to communicate. The basic objective of this project is to develop a computer based intelligent system that will enable mute people significantly to communicate with all other people using their natural hand gestures.
The idea consisted of designing and building up an intelligent system using image processing, machine learning and artificial intelligence concepts to take visual inputs of sign language’s hand gestures and generate easily recognizable form of outputs.
Hence the objective of this project is to develop an intelligent system which can act as a translator between the sign language and the spoken language dynamically and can make the communication between people with mute and normal people both effective and efficient. The system is we are implementing for Binary sign language but it can detect any sign language with prior image processing.
Use of Wavelet Transform Extension for Graphics Image Compression using JPEG2...CSCJournals
The new image compression standard JPEG2000, provides high compression rates for the same visual quality for gray and color images than JPEG. JPEG2000 is being adopted for image compression and transmission in mobile phones, PDA and computers. An image may contain the formatted text and graphics data. The compression performance of the JPEG2000 behaves poorly when compressing an image with low color depth such as graphics images. In this paper, we propose a technique to distinguish the true color images from graphics images and to compress graphics images using a simplified JPEG2000 compression method that will improve the compression performance. This method can be easily adapted in image compression applications without changing the syntax of compressed stream.
User Interactive Color Transformation between ImagesIJMER
Abstract: In this paper we present a process called color
transfer which can borrow one image’s color
characteristics from another. Most current colorization
algorithms either require a significant user effort or have
large computational time. Here focus on orthogonal color
space i.e. lαβ color space without correlation between the
axes is given. Here we have implemented two global color
transfer algorithms in lαβ color space using simple color
statistical information such as mean, standard deviation
and covariance between the pixels of image. Our approach
is the extension of Reinhard's. Our local color transfer
algorithm uses simple color statistical analysis to recolor
the target image according to selected color range in
source image. Target image’s color influence mask is
prepared. It is a mask that specifies what parts of target
image will be affected according to selected color range.
After that target image is recolored in lαβ color space
according to prepared color influence map. In the lαβ
color space luminance and chrominance information is
separate so it allows making image recoloring optional.
The basic color transformation uses stored color statistics
of source and target image. All the algorithms are
implemented in JAVA object oriented language. The main
advantage of proposed method over the existing one is it
allows the user to recolor a part of the image in a simple &
intuitive way, preserving other color intact & achieving
natural look.
Index Terms: color transfer, local color statistics, color
characteristics, orthogonal color space, color influence
map.
Wondering about using PNG or JPG or BMP or GIF. This presentation will answer all your queries related to designing digital images and which formats are best while saving them..
Terms like raster images, vector images, vectors, alpha channels, transparency, palettes, compression are explained here.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
JMeter webinar - integration with InfluxDB and GrafanaRTTS
Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics.
Length: 30 minutes
Session Overview
-------------------------------------------
During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
- What are the benefits of integrating InfluxDB and Grafana into the load testing stack?
- Which features are provided by Grafana?
- Demonstration of InfluxDB and Grafana using a practice web application
To view the webinar recording, go to:
https://www.rttsweb.com/jmeter-integration-webinar
Generating a custom Ruby SDK for your web service or Rails API using Smithyg2nightmarescribd
Have you ever wanted a Ruby client API to communicate with your web service? Smithy is a protocol-agnostic language for defining services and SDKs. Smithy Ruby is an implementation of Smithy that generates a Ruby SDK using a Smithy model. In this talk, we will explore Smithy and Smithy Ruby to learn how to generate custom feature-rich SDKs that can communicate with any web service, such as a Rails JSON API.