Exponential-Golomb coding (also known as Exp-Golomb coding) is a form of entropy coding used primarily in applications such as video coding (e.g., in the H.264/MPEG-4 AVC standard) and other data compression schemes. It is particularly effective for encoding integers and is designed to efficiently represent small values while allowing for larger values to be represented as well.
Even–Rodeh coding is a type of error-correcting code that is used in the realm of digital communication and data storage. It is named after its inventors, Israeli mathematicians Shimon Even and David Rodeh. The primary purpose of this coding scheme is to detect and correct errors that may occur during the transmission or storage of data. The Even–Rodeh code is structured in a way that it can efficiently correct multiple bit errors in a codeword.
Error Level Analysis (ELA) is a technique used in digital forensics and image analysis for detecting alterations in digital images. The basic premise behind ELA is that when an image is manipulated or edited, the compression levels of the modified areas may differ from the original areas. This is particularly relevant for images that are saved in lossy formats like JPEG. ### How ELA Works: 1. **Image Compression**: Digital images are often compressed to reduce file size.
Entropy coding is a type of lossless data compression technique that encodes data based on the statistical frequency of symbols. It uses the principle of entropy from information theory, which quantifies the amount of unpredictability or information content in a set of data. The goal of entropy coding is to represent data in a more efficient way, reducing the overall size of the data without losing any information.
Embedded Zerotrees of Wavelet Transforms (EZW) is a compression technique that leverages the properties of wavelet transforms to efficiently encode signals and images. It is particularly useful for compressing images due to its ability to exploit spatial redundancies and perceptual characteristics of human vision. ### Key Concepts: 1. **Wavelet Transform**: - Wavelet transforms decompose a signal or image into different frequency components at multiple scales.
Elias omega coding is a universal coding scheme used to encode positive integers in a variable-length binary format. It is part of the family of Elias codes, which are used in information theory for efficient representation of numbers. Elias omega coding is particularly effective for encoding larger integers due to its recursive structure.
Elias gamma coding is a universal code used for encoding non-negative integers in a way that is both efficient and easy to decode. It is particularly useful in data compression and communication protocols. The primary goal of Elias gamma coding is to represent integers in a way that allows for a variable-length representation, optimizing space based on the size of the number being encoded.
Elias delta coding is a variable-length prefix coding scheme used for encoding integers, particularly useful in applications such as data compression and efficient numeral representation. It is part of a family of Elias codes, which also includes Elias gamma and Elias omega coding. The Elias delta coding scheme consists of the following steps for encoding a positive integer \( n \): 1. **Binary Representation**: First, determine the binary representation of the integer \( n \).
Dynamic Markov Compression is a technique used in information theory and data compression that leverages the principles of Markov models to achieve efficient compression of data sequences. Here's an overview of the key components and concepts associated with this approach: ### Key Concepts: 1. **Markov Models**: A Markov model is a statistical model that represents a system which transitions between states based on certain probabilities.
Dyadic distribution refers to a specific statistical distribution that deals with the probabilities associated with pairs (dyads) of categorical data, often used in social sciences, network analysis, and mathematical statistics. The term can also relate to dyadic relationships in various settings, such as in psychology, sociology, or ecology, where it may explore relationships between two entities or components. In statistics, dyadic distributions may represent joint distributions of two random variables, capturing the dependencies between them.
DriveSpace is a disk compression utility that was used in Microsoft DOS and early versions of Windows, specifically in Windows 95 and Windows 98. It allowed users to create virtual drives by compressing files and directories on their hard drives, effectively increasing the amount of usable storage space. DriveSpace worked by compressing files on the disk and storing them in a way that would allow for compressed data to be accessed quickly.
Display resolution refers to the amount of detail that an image can hold and is typically defined by the number of pixels in each dimension that can be displayed. It is expressed in terms of width x height, with both measurements given in pixels. For example, a display resolution of 1920 x 1080 means the screen has 1920 pixels horizontally and 1080 pixels vertically. Higher resolutions generally allow for clearer and sharper images, as more pixels can represent finer details.
Differential Pulse-Code Modulation (DPCM) is a signal encoding technique used primarily in audio and video compression, as well as in digital communications. It is an extension of Pulse-Code Modulation (PCM) and is specifically designed to reduce the bit rate required for transmission by exploiting the correlation between successive samples. ### How DPCM Works: 1. **Prediction**: DPCM predicts the current sample value based on previous samples.
A dictionary coder is a type of data compression algorithm that replaces frequently occurring sequences of data (such as strings, phrases, or patterns) with shorter, unique codes or identifiers. This technique is often used in lossless data compression to reduce the size of data files while preserving the original information. The coder builds a dictionary of these sequences during the encoding process, using it to replace instances of those sequences in the data being compressed.
Delta encoding is a data compression technique that stores data as the difference (the "delta") between sequential data rather than storing the complete data set. This method is particularly effective in scenarios where data changes incrementally over time, as it can significantly reduce the amount of storage space needed by only recording changes instead of the entire dataset.
Deflate is a data compression algorithm that is used to reduce the size of data for storage or transmission. It combines two primary techniques: the LZ77 algorithm, which is a lossless data compression method that replaces repeated occurrences of data with references to a single copy, and Huffman coding, which is a variable-length coding scheme that assigns shorter codes to more frequently occurring characters and longer codes to rarer ones.
A deblocking filter is a post-processing technique used in video compression for reducing visible blockiness that can occur during the compression of video content, particularly in formats like H.264 or HEVC (H.265). When video is compressed, it is often divided into small blocks (macroblocks or coding units).
Data deduplication is a process used in data management to eliminate duplicate copies of data to reduce storage needs and improve efficiency. This technique is particularly valuable in environments where large volumes of data are generated or backed up, such as in data centers, cloud storage, and backup solutions.
Data compression symmetry refers to the idea that the processes of data compression and decompression exhibit a form of symmetry in their relationship. In the context of information theory and data encoding, this concept can manifest in different ways. ### Key Aspects of Data Compression Symmetry: 1. **Reciprocal Operations**: The processes of compression and decompression are mathematically reciprocal. Data compression reduces the size of a dataset, while decompression restores the dataset to its original form (or a close approximation).
The **data compression ratio** is a measure that quantifies the effectiveness of a data compression method. It indicates how much the data size is reduced after compression.