Design of a digital compression technique for shuttle television

The determination of the performance and hardware complexity of data compression algorithms applicable to color television signals, were studied to assess the feasibility of digital compression techniques for shuttle communications applications. For return link communications, it is shown that a nonadaptive two dimensional DPCM technique compresses the bandwidth of field-sequential color TV to about 13 MBPS and requires less than 60 watts of secondary power. For forward link communications, a facsimile coding technique is recommended which provides high resolution slow scan television on a 144 KBPS channel. The onboard decoder requires about 19 watts of secondary power

A study of data coding technology developments in the 1980-1985 time frame, volume 2

The source parameters of digitized analog data are discussed. Different data compression schemes are outlined and analysis of their implementation are presented. Finally, bandwidth compression techniques are given for video signals

Data compression techniques applied to high resolution high frame rate video technology

An investigation is presented of video data compression applied to microgravity space experiments using High Resolution High Frame Rate Video Technology (HHVT). An extensive survey of methods of video data compression, described in the open literature, was conducted. The survey examines compression methods employing digital computing. The results of the survey are presented. They include a description of each method and assessment of image degradation and video data parameters. An assessment is made of present and near term future technology for implementation of video data compression in high speed imaging system. Results of the assessment are discussed and summarized. The results of a study of a baseline HHVT video system, and approaches for implementation of video data compression, are presented. Case studies of three microgravity experiments are presented and specific compression techniques and implementations are recommended

Implementation of JPEG compression and motion estimation on FPGA hardware

A hardware implementation of JPEG allows for real-time compression in data intensivve applications, such as high speed scanning, medical imaging and satellite image transmission. Implementation options include dedicated DSP or media processors, FPGA boards, and ASICs. Factors that affect the choice of platform selection involve cost, speed, memory, size, power consumption, and case of reconfiguration. The proposed hardware solution is based on a Very high speed integrated circuit Hardware Description Language (VHDL) implememtation of the codec with prefered realization using an FPGA board due to speed, cost and flexibility factors; The VHDL language is commonly used to model hardware impletations from a top down perspective. The VHDL code may be simulated to correct mistakes and subsequently synthesized into hardware using a synthesis tool, such as the xilinx ise suite. The same VHDL code may be synthesized into a number of sifferent hardware architetcures based on constraints given. For example speed was the major constraint when synthesizing the pipeline of jpeg encoding and decoding, while chip area and power consumption were primary constraints when synthesizing the on-die memory because of large area. Thus, there is a trade off between area and speed in logic synthesis

Study of on-board compression of earth resources data

The current literature on image bandwidth compression was surveyed and those methods relevant to compression of multispectral imagery were selected. Typical satellite multispectral data was then analyzed statistically and the results used to select a smaller set of candidate bandwidth compression techniques particularly relevant to earth resources data. These were compared using both theoretical analysis and simulation, under various criteria of optimality such as mean square error (MSE), signal-to-noise ratio, classification accuracy, and computational complexity. By concatenating some of the most promising techniques, three multispectral data compression systems were synthesized which appear well suited to current and future NASA earth resources applications. The performance of these three recommended systems was then examined in detail by all of the above criteria. Finally, merits and deficiencies were summarized and a number of recommendations for future NASA activities in data compression proposed

Real-time data compression of broadcast video signals

A non-adaptive predictor, a nonuniform quantizer, and a multi-level Huffman coder are incorporated into a differential pulse code modulation system for coding and decoding broadcast video signals in real time

Sparse Modeling for Image and Vision Processing

In recent years, a large amount of multi-disciplinary research has been conducted on sparse models and their applications. In statistics and machine learning, the sparsity principle is used to perform model selection---that is, automatically selecting a simple model among a large collection of them. In signal processing, sparse coding consists of representing data with linear combinations of a few dictionary elements. Subsequently, the corresponding tools have been widely adopted by several scientific communities such as neuroscience, bioinformatics, or computer vision. The goal of this monograph is to offer a self-contained view of sparse modeling for visual recognition and image processing. More specifically, we focus on applications where the dictionary is learned and adapted to data, yielding a compact representation that has been successful in various contexts.Comment: 205 pages, to appear in Foundations and Trends in Computer Graphics and Visio