This document provides definitions and explanations of various file formats and compression techniques, including:
- Lossless vs lossy data compression
- Raster images and how color depth affects stored color values
- Image glitching techniques like imagebending and databending
- How bytes and binary files are structured
- Components of image files like headers, channels, and interleaved vs non-interleaved formats
- Explanations of formats like BMP, GIF, PNG, PSD, JPG, TIFF, and others
Abstract
Field of image processing has vast applications in medical, forensic, research etc., It includes various domains like enhancement,
classification, segmentation, etc., which are widely used for these applications. Image Enhancement is the pre processing step on
which the accuracy of the result lies. Image enhancement aims to improve the visual appearance of an image, without affecting
the original attributes (i.e.,) image contrast is adjusted and noise is removed to produce better quality image. Hence image
enhancement is one of the most important tasks in image processing. Enhancement is classified into two categories spatial domain
enhancement and frequency domain enhancement. Spatial domain enhancement acts upon pixel value whereas frequency domain
enhancement acts on the Fourier transform of the image. The enhancement techniques to be used depend on modality, climatic
and visual perspective etc., In this paper, we present a survey on various existing image enhancement techniques.
Keywords: Enhancement, Spatial domain enhancement, Frequency domain enhancement, Contrast, Modality.
Abstract
Field of image processing has vast applications in medical, forensic, research etc., It includes various domains like enhancement,
classification, segmentation, etc., which are widely used for these applications. Image Enhancement is the pre processing step on
which the accuracy of the result lies. Image enhancement aims to improve the visual appearance of an image, without affecting
the original attributes (i.e.,) image contrast is adjusted and noise is removed to produce better quality image. Hence image
enhancement is one of the most important tasks in image processing. Enhancement is classified into two categories spatial domain
enhancement and frequency domain enhancement. Spatial domain enhancement acts upon pixel value whereas frequency domain
enhancement acts on the Fourier transform of the image. The enhancement techniques to be used depend on modality, climatic
and visual perspective etc., In this paper, we present a survey on various existing image enhancement techniques.
Keywords: Enhancement, Spatial domain enhancement, Frequency domain enhancement, Contrast, Modality.
COM2304: Intensity Transformation and Spatial Filtering – I (Intensity Transf...Hemantha Kulathilake
At the end of this lesson, you should be able to;
describe spatial domain of the digital image.
recognize the image enhancement techniques.
describe and apply the concept of intensity transformation.
express histograms and histogram processing.
describe image noise.
characterize the types of Noise.
describe concept of image restoration.
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
COM2304: Intensity Transformation and Spatial Filtering – III Spatial Filters...Hemantha Kulathilake
At the end of this lecture, you should be able to;
describe sharpening through spatial filters.
Identify usage of derivatives in Image Processing.
discuss edge detection techniques.
compare 1st & 2nd order derivatives used for sharpening.
Apply sharpening techniques for problem solving.
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
COM2304: Intensity Transformation and Spatial Filtering – I (Intensity Transf...Hemantha Kulathilake
At the end of this lesson, you should be able to;
describe spatial domain of the digital image.
recognize the image enhancement techniques.
describe and apply the concept of intensity transformation.
express histograms and histogram processing.
describe image noise.
characterize the types of Noise.
describe concept of image restoration.
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
COM2304: Intensity Transformation and Spatial Filtering – III Spatial Filters...Hemantha Kulathilake
At the end of this lecture, you should be able to;
describe sharpening through spatial filters.
Identify usage of derivatives in Image Processing.
discuss edge detection techniques.
compare 1st & 2nd order derivatives used for sharpening.
Apply sharpening techniques for problem solving.
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
This presentation is about JPEG compression algorithm. It briefly describes all the underlying steps in JPEG compression like picture preparation, DCT, Quantization, Rendering and Encoding.
I am happy to announce my new solo show at the Fabio Paris Art Gallery in Brescia, Italy, curated by Domenico Quaranta. It is a small but very nice gallery that also hosts artists like UBERMORGEN.COM, Eva e Franco Mattes aka 0100101110101101.ORG and my friends Nullsleep and Tonylight - so I am in realy good company.
This is the Catalogue written by Domenico Quaranta.
Climate Impact of Software Testing at Nordic Testing DaysKari Kakkonen
My slides at Nordic Testing Days 6.6.2024
Climate impact / sustainability of software testing discussed on the talk. ICT and testing must carry their part of global responsibility to help with the climat warming. We can minimize the carbon footprint but we can also have a carbon handprint, a positive impact on the climate. Quality characteristics can be added with sustainability, and then measured continuously. Test environments can be used less, and in smaller scale and on demand. Test techniques can be used in optimizing or minimizing number of tests. Test automation can be used to speed up testing.
Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...SOFTTECHHUB
The choice of an operating system plays a pivotal role in shaping our computing experience. For decades, Microsoft's Windows has dominated the market, offering a familiar and widely adopted platform for personal and professional use. However, as technological advancements continue to push the boundaries of innovation, alternative operating systems have emerged, challenging the status quo and offering users a fresh perspective on computing.
One such alternative that has garnered significant attention and acclaim is Nitrux Linux 3.5.0, a sleek, powerful, and user-friendly Linux distribution that promises to redefine the way we interact with our devices. With its focus on performance, security, and customization, Nitrux Linux presents a compelling case for those seeking to break free from the constraints of proprietary software and embrace the freedom and flexibility of open-source computing.
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.
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Albert Hoitingh
In this session I delve into the encryption technology used in Microsoft 365 and Microsoft Purview. Including the concepts of Customer Key and Double Key Encryption.
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
PHP Frameworks: I want to break free (IPC Berlin 2024)Ralf Eggert
In this presentation, we examine the challenges and limitations of relying too heavily on PHP frameworks in web development. We discuss the history of PHP and its frameworks to understand how this dependence has evolved. The focus will be on providing concrete tips and strategies to reduce reliance on these frameworks, based on real-world examples and practical considerations. The goal is to equip developers with the skills and knowledge to create more flexible and future-proof web applications. We'll explore the importance of maintaining autonomy in a rapidly changing tech landscape and how to make informed decisions in PHP development.
This talk is aimed at encouraging a more independent approach to using PHP frameworks, moving towards a more flexible and future-proof approach to PHP development.
Le nuove frontiere dell'AI nell'RPA con UiPath Autopilot™UiPathCommunity
In questo evento online gratuito, organizzato dalla Community Italiana di UiPath, potrai esplorare le nuove funzionalità di Autopilot, il tool che integra l'Intelligenza Artificiale nei processi di sviluppo e utilizzo delle Automazioni.
📕 Vedremo insieme alcuni esempi dell'utilizzo di Autopilot in diversi tool della Suite UiPath:
Autopilot per Studio Web
Autopilot per Studio
Autopilot per Apps
Clipboard AI
GenAI applicata alla Document Understanding
👨🏫👨💻 Speakers:
Stefano Negro, UiPath MVPx3, RPA Tech Lead @ BSP Consultant
Flavio Martinelli, UiPath MVP 2023, Technical Account Manager @UiPath
Andrei Tasca, RPA Solutions Team Lead @NTT Data
SAP Sapphire 2024 - ASUG301 building better apps with SAP Fiori.pdfPeter Spielvogel
Building better applications for business users with SAP Fiori.
• What is SAP Fiori and why it matters to you
• How a better user experience drives measurable business benefits
• How to get started with SAP Fiori today
• How SAP Fiori elements accelerates application development
• How SAP Build Code includes SAP Fiori tools and other generative artificial intelligence capabilities
• How SAP Fiori paves the way for using AI in SAP apps
zkStudyClub - Reef: Fast Succinct Non-Interactive Zero-Knowledge Regex ProofsAlex Pruden
This paper presents Reef, a system for generating publicly verifiable succinct non-interactive zero-knowledge proofs that a committed document matches or does not match a regular expression. We describe applications such as proving the strength of passwords, the provenance of email despite redactions, the validity of oblivious DNS queries, and the existence of mutations in DNA. Reef supports the Perl Compatible Regular Expression syntax, including wildcards, alternation, ranges, capture groups, Kleene star, negations, and lookarounds. Reef introduces a new type of automata, Skipping Alternating Finite Automata (SAFA), that skips irrelevant parts of a document when producing proofs without undermining soundness, and instantiates SAFA with a lookup argument. Our experimental evaluation confirms that Reef can generate proofs for documents with 32M characters; the proofs are small and cheap to verify (under a second).
Paper: https://eprint.iacr.org/2023/1886
Pushing the limits of ePRTC: 100ns holdover for 100 daysAdtran
At WSTS 2024, Alon Stern explored the topic of parametric holdover and explained how recent research findings can be implemented in real-world PNT networks to achieve 100 nanoseconds of accuracy for up to 100 days.
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.
Elevating Tactical DDD Patterns Through Object CalisthenicsDorra BARTAGUIZ
After immersing yourself in the blue book and its red counterpart, attending DDD-focused conferences, and applying tactical patterns, you're left with a crucial question: How do I ensure my design is effective? Tactical patterns within Domain-Driven Design (DDD) serve as guiding principles for creating clear and manageable domain models. However, achieving success with these patterns requires additional guidance. Interestingly, we've observed that a set of constraints initially designed for training purposes remarkably aligns with effective pattern implementation, offering a more ‘mechanical’ approach. Let's explore together how Object Calisthenics can elevate the design of your tactical DDD patterns, offering concrete help for those venturing into DDD for the first time!
In his public lecture, Christian Timmerer provides insights into the fascinating history of video streaming, starting from its humble beginnings before YouTube to the groundbreaking technologies that now dominate platforms like Netflix and ORF ON. Timmerer also presents provocative contributions of his own that have significantly influenced the industry. He concludes by looking at future challenges and invites the audience to join in a discussion.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
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.
Securing your Kubernetes cluster_ a step-by-step guide to success !
//STEIM Workshop: A Vernacular of File Formats
1. “A Vernacular of File Formats and Extra Files”
Kim Asendorf (DE) and Rosa Menkman (NL)
2. Lossless data compression is a class of data compression algorithms
that allows the exact original data to be reconstructed from the compressed data.
"lossy" compression is a data encoding method which compresses data by
discarding (losing) some of it.
Define Your Terms(or: Kanye West Fucked Up My Show)
3. A raster image ( vs. vector images and stereo images) is a data structure generally
represented by a rectangular grid of pixels (or a bitmap).
Technically, a bitmap is characterized by a certain amount of pixels defining the
images width and height AND the amount of bits per pixel that defines the images
color depth.
Gamut: the possible different color representations.
When an image has a relatively low color depth, the stored color value is typically a
number represented within an index of a color map or palette.
Define Your Terms(or: Kanye West Fucked Up My Show)
5. 8bits = 1byte
A binary file = a sequence of bytes.
a binary file often also contains formatting information.
compiled it can for instance form a program, or any other kind of file format.
A hex editor (0xED) can be used to view file data as a sequence of hexadecimal
(or decimal, binary or ASCII character) values
for corresponding bytes of a binary file.
If a binary file is opened in a text editor, each group of eight bits will typically be
translated as a single character, and you will see a (probably unintelligible) display
of textual characters.
If the file is opened in some other application, that application will have its own use
for each byte: maybe the application will treat each byte as a number and output a
stream of numbers between 0 and 255 — or maybe interpret the numbers in the
bytes as colors and display the corresponding picture.
Define Your Terms(or: Kanye West Fucked Up My Show)
6. Header: the data placed at the beginning of a block of data (in this case the image)
being stored or transmitted.
interleaved vs non-interleaved
The interleaved raw format stores its RGB data
rgbrgbrgbrgbrgbrgbrgbrgbrgb
A planar (non-interleaved) format stores its data:
rrrrrrrrrgggggggggbbbbbbbbb
Photoshop RAW
flat binary (header = 0)
7. Photoshop RAW
flat binary (header = 0)
A channel is the grayscale image of the same size as a color image, made of just
one of these primary colors. For instance, an image from a standard digital camera
will have a red, green and blue channel. A grayscale image has just one channel.
8.
9. Wordpad effect pietjepuk666 & Stallio:
(open as unicode - mac os Roman) does at least two things to a binary file.
“I've found that Wordpad does at least two things to a binary file; it replaces byte
07 (ascii: BEEP) with 20 - a space - , and it replaces every lonely 0A or 0D (line
feed - end of line - and carriage return - new line of text - respectively) and also
0B (vertical tab) with the bytes "0D 0A". So the rate of glitching is probably
dependent on how dark the picture is, since low bytes like these give dark pixels (i
suppose).
in short: everytime it adds one byte.”
BMP
BMP is an uncompressed file format.
imagebending vs databending
12. GIF
(8bit color depth, interlaced - 2f replaced for c0)
Graphics Interchange Format is a bitmap image format that supports 8 bits per pixel
and can thus consist of no more then 256 colors.
The format supports animation.
Dither (the grainy blocky artifacts) is an intentionally applied form of noise used to
“randomize quantization error”; the difference between the actual analog value and
quantized digital value. This error is caused by truncation (the discarding of less
significant information).
Dither thus helps to prevent from large-scale patterns such as "banding" (stepwise
rendering of smooth gradations in brightness or hue). Moreover, the not available
colors are approximated because the human eye perceives the diffusion as a mixture
of the colors. This creates the illusion of color depth.
13. GIF
(8bit color depth, interlaced - 2f replaced for c0)
The gif format uses a 4 pass one dimensional interlacing strategy. This means that
one half of the image, consisting of every other row of pixels is rendered after the
other half. In the image on the left this shows through a gradual displacement during
weaving (the putting together of the two layers), which resulted in a second “ghost
image” (or combing artifacts with jagged edges).
17. PNG
(8bit color depth, interlaced - 2f replaced for c0)
PNG is a bitmapped image format that employs lossless data compression and
offers a 7-pass 2-dimensional interlacing scheme—the Adam7 algorithm.
This is more sophisticated than GIF's 1-dimensional, 4-pass scheme, and often
allows for a clearer low-resolution image to be visible earlier in the transfer. This is
visible in image 1 which just passed its first stage of the 7 part interlacing scheme.
In this stage a part of the image is rendered almost flawless, while the further it gets
rendered, the more the corrupted data becomes visible.
20. A JPG compression consists of 6 subsequent steps:
1. Color space transformation
2. Downsampling
3. Block splitting
4. Discrete cosine transform
5. Quantization
6. Entropy coding
LOSSY: JPG
21. 1. Initially, images have to be transformed from the RGB color space to
another color space (called Y′CbCr), Here the Y refers to the luma or
brightness and the Cb and Cr values stand for the chroma or color
values for the blue and the red channel.
2. Because the human eye doesn’t perceives small differences within the
Cb and Cr space very well, these elements are downsampled.
3. After the color space transformation, the image is split into tiles or
macroblocks. Rectangular regions of the image that are transformed and
encoded separately.
4. Next, a Discrete Cosine Transform (which works similar to the Fourier
Transform function, exploited in datamoshing and macroblock studies) is
used to create a frequency spectrum, to transform the
8×8 blocks to a combination of the 64 two-dimensional DCT basis
functions or patterns (as differentiated by the red lines).
5. During the Quantization step, the highest brightness-frequency
variations become a base line (or 0-value), while small positive and
negative frequency differentiations get a value, which take many fewer
bits to represent.
22. Because the RGB color values are described in such
a complex algorithms, some random data replacement often results into
dramatic discoloration and other effects.
The very high compression ratio of this jpg effects the quality of the image
and the size of the artifacts.
When using quantization with block-based coding, as in these JPEG-
compressed images, several types of
often unwanted artifacts can appear, for instance ringing or ghosting. In the
bend image to the left, the low quality and corruption have made these
artifacts more apparent.
6. finally, entropy coding is applied. Entropy coding is a special form of
lossless data compression that involves arranging the image components in a
"zigzag" order. This allows the quantized coefficient table to be rewritten in a
zigzag order to a sequence of frequencies.
A run-length encoding (RLE) algorithm groups similar frequencies together and
after that, via "Huffman coding" organizes what is left.
23. While sequential encoding (or baseline) encodes coefficients of a single block
at a time (in a zigzag manner), progressive encoding encodes similar-
positioned coefficients of all blocks in one go, followed by the next
positioned coefficients of all blocks, and so on.
JPG
(progressive)
26. The JPEG 2000 standard was mainly developed because of the many
edge and blocking artifacts of the JPG format. JPEG 2000 has
“improved scalability and edit-ability”.
In JPG 2000, after the color transformation step, the image is split into
so-called tiles, rectangular regions of the image that are transformed and
encoded separately.
Tiles can be any size, and it is also possible to consider the whole
image as one single tile. This results into a collection of sub-bands
which represent several approximation scales.
JPG 2000
27.
28. TARGA
The gif format uses a 4 pass one dimensional interlacing strategy. This means that
one half of the image, consisting of every other row of pixels is rendered after the
other half. In the image on the left this shows through a gradual displacement during
weaving (the putting together of the two layers), which resulted in a second “ghost
image” (or combing artifacts with jagged edges).