Author: Mark Dee HetheringtonPublisher:
ISBN:
Category :
Languages : en
Pages : 298
Book Description
Image Compression Using Vector Quantization and Lossless Index Coding
Author: Mark Dee HetheringtonPublisher:
ISBN:
Category :
Languages : en
Pages : 298
Book Description
Vector Quantization and Signal Compression
Author: Allen GershoPublisher: Springer Science & Business Media
ISBN: 0792391810
Category : Technology & Engineering
Languages : en
Pages : 762
Book Description
Herb Caen, a popular columnist for the San Francisco Chronicle, recently quoted a Voice of America press release as saying that it was reorganizing in order to "eliminate duplication and redundancy. " This quote both states a goal of data compression and illustrates its common need: the removal of duplication (or redundancy) can provide a more efficient representation of data and the quoted phrase is itself a candidate for such surgery. Not only can the number of words in the quote be reduced without losing informa tion, but the statement would actually be enhanced by such compression since it will no longer exemplify the wrong that the policy is supposed to correct. Here compression can streamline the phrase and minimize the em barassment while improving the English style. Compression in general is intended to provide efficient representations of data while preserving the essential information contained in the data. This book is devoted to the theory and practice of signal compression, i. e. , data compression applied to signals such as speech, audio, images, and video signals (excluding other data types such as financial data or general purpose computer data). The emphasis is on the conversion of analog waveforms into efficient digital representations and on the compression of digital information into the fewest possible bits. Both operations should yield the highest possible reconstruction fidelity subject to constraints on the bit rate and implementation complexity.
Video Image Compression Using Subband Coding and Vector Quantization
Author: Eric Kwok-Leong LoDigital Image Compression Techniques
Author: Majid RabbaniPublisher: SPIE Press
ISBN: 9780819406484
Category : Computers
Languages : en
Pages : 248
Book Description
In order to utilize digital images effectively, specific techniques are needed to reduce the number of bits required for their representation. This Tutorial Text provides the groundwork for understanding these image compression tecniques and presents a number of different schemes that have proven useful. The algorithms discussed in this book are concerned mainly with the compression of still-frame, continuous-tone, monochrome and color images, but some of the techniques, such as arithmetic coding, have found widespread use in the compression of bilevel images. Both lossless (bit-preserving) and lossy techniques are considered. A detailed description of the compression algorithm proposed as the world standard (the JPEG baseline algorithm) is provided. The book contains approximately 30 pages of reconstructed and error images illustrating the effect of each compression technique on a consistent image set, thus allowing for a direct comparison of bit rates and reconstucted image quality. For each algorithm, issues such as quality vs. bit rate, implementation complexity, and susceptibility to channel errors are considered.
Lossless Information Hiding in Images
Author: Zhe-Ming LuPublisher: Syngress
ISBN: 0128121661
Category : Computers
Languages : en
Pages : 434
Book Description
Lossless Information Hiding in Images introduces many state-of-the-art lossless hiding schemes, most of which come from the authors' publications in the past five years. After reading this book, readers will be able to immediately grasp the status, the typical algorithms, and the trend of the field of lossless information hiding. Lossless information hiding is a technique that enables images to be authenticated and then restored to their original forms by removing the watermark and replacing overridden images. This book focuses on the lossless information hiding in our most popular media, images, classifying them in three categories, i.e., spatial domain based, transform domain based, and compressed domain based. Furthermore, the compressed domain based methods are classified into VQ based, BTC based, and JPEG/JPEG2000 based. - Focuses specifically on lossless information hiding for images - Covers the most common visual medium, images, and the most common compression schemes, JPEG and JPEG 2000 - Includes recent state-of-the-art techniques in the field of lossless image watermarking - Presents many lossless hiding schemes, most of which come from the authors' publications in the past five years
Image and Video Compression
Author: Madhuri A. JoshiPublisher: CRC Press
ISBN: 148222822X
Category : Computers
Languages : en
Pages : 242
Book Description
Image and video signals require large transmission bandwidth and storage, leading to high costs. The data must be compressed without a loss or with a small loss of quality. Thus, efficient image and video compression algorithms play a significant role in the storage and transmission of data. Image and Video Compression: Fundamentals, Techniques, and Applications explains the major techniques for image and video compression and demonstrates their practical implementation using MATLAB® programs. Designed for students, researchers, and practicing engineers, the book presents both basic principles and real practical applications. In an accessible way, the book covers basic schemes for image and video compression, including lossless techniques and wavelet- and vector quantization-based image compression and digital video compression. The MATLAB programs enable readers to gain hands-on experience with the techniques. The authors provide quality metrics used to evaluate the performance of the compression algorithms. They also introduce the modern technique of compressed sensing, which retains the most important part of the signal while it is being sensed.
JPEG2000 Image Compression Fundamentals, Standards and Practice
Author: David TaubmanPublisher: Springer Science & Business Media
ISBN: 1461507995
Category : Computers
Languages : en
Pages : 780
Book Description
This is nothing less than a totally essential reference for engineers and researchers in any field of work that involves the use of compressed imagery. Beginning with a thorough and up-to-date overview of the fundamentals of image compression, the authors move on to provide a complete description of the JPEG2000 standard. They then devote space to the implementation and exploitation of that standard. The final section describes other key image compression systems. This work has specific applications for those involved in the development of software and hardware solutions for multimedia, internet, and medical imaging applications.
Structured Vector Quantizers in Image Coding
Author: Manijeh KhataiePublisher:
ISBN:
Category : Data compression (Telecommunication)
Languages : en
Pages : 0
Book Description
Image data compression is concerned with the minimization of the volume of data used to represent an image. In recent years, image compression algorithms using Vector Quantization (VQ) have been receiving considerable attention. Unstructured vector quantizers, i.e., those with no restriction on the geometrical structure of the codebook, suffer from two basic drawbacks, viz., the codebook search complexity and the large storage requirement. This explains the interest in the structured VQ schemes, such as lattice-based VQ and multi-stage VQ. The objective of this thesis is to devise techniques to reduce the complexity of vector quantizers. In order to reduce the codebook search complexity and memory requirement, a universal Gaussian codebook in a residual VQ or a lattice-based VQ is used. To achieve a better performance, a part of work has been done in the frequency domain. Specifically, in order to retain the high-frequency coefficients in transform coding, two methods are suggested. One is developed for moderate to high rate data compression while the other is effective for low to moderate data rate. In the first part of this thesis, a residual VQ using a low rate optimal VQ in the first-stage and a Gaussian codebook in the other stages are introduced. From rate distortion theory, for most memoryless sources and many Gaussian sources with memory, the quantization error under MSE criterion, for small distortion, is memoryless and Gaussian. For VQ with a realistic rate, the error signal has a non-Gaussian distribution. It is shown that the distribution of locally normalized error signals, however, becomes close to a Gaussian distribution. In the second part, a new two-stage quantizer is proposed. The function of the first stage is to encode the more important low-pass components of the image and that of the second is to do the same for the high-frequency components ignored in the first stage. In one scheme, a high-rate lattice-based vector quantizer is used as the quantizer for both stages. In another scheme, the standard JPEG with a low rate is used as the quantizer of the first stage, and a lattice-based VQ is used for the second stage. The resulting bit rate of the two-stage lattice-based VQ in either scheme is found to be considerably better than that of JPEG for moderate to high bit rates. In the third part of the thesis, a method to retain the high-frequency coefficients is proposed by using a relatively huge codebook obtained by truncating the lattices with a large radius. As a result, a large number of points fall inside the boundary of the codebook, and thus, the images are encoded with high quality and low complexity: To reduce the bit rate, a shorter representation is assigned to the more frequently used lattice points. To index the large number of lattice points which fall inside the boundary, two methods that are based on grouping of the lattice points according to their frequencies of occurrence are proposed. For most of the test images, the proposed methods of retaining high-frequency coefficients is found to outperform JPEG.
Image and Text Compression
Author: James A. StorerPublisher: Springer Science & Business Media
ISBN: 1461535964
Category : Technology & Engineering
Languages : en
Pages : 355
Book Description
James A. Storer Computer Science Dept. Brandeis University Waltham, MA 02254 Data compression is the process of encoding a body of data to reduce stor age requirements. With Lossless compression, data can be decompressed to be identical to the original, whereas with lossy compression, decompressed data may be an acceptable approximation (according to some fidelity criterion) to the original. For example, with digitized video, it may only be necessary that the decompressed video look as good as the original to the human eye. The two primary functions of data compression are: Storage: The capacity of a storage device can be effectively increased with data compression software or hardware that compresses a body of data on its way to the storage device and decompress it when it is retrieved. Communications: The bandwidth of a digital communication link can be effectively increased by compressing data at the sending end and decom pressing data at the receiving end. Here it can be crucial that compression and decompression can be performed in real time.
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