Author: Syed A. RizviPublisher:
ISBN:
Category :
Languages : en
Pages : 320
Book Description
High-compression Image Coding Using Predictive Residual Vector Quantization
Author: Syed A. RizviVector 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.
Recursive Block Coding for Image Data Compression
Author: Paul M. FarrellePublisher: Springer Science & Business Media
ISBN: 146139676X
Category : Computers
Languages : en
Pages : 321
Book Description
Recursive Block Coding, a new image data compression technique that has its roots in noncausal models for 1d and 2d signals, is the subject of this book. The underlying theory provides a multitude of compression algorithms that encompass two course coding, quad tree coding, hybrid coding and so on. Since the noncausal models provide a fundamentally different image representation, they lead to new approaches to many existing algorithms, including useful approaches for asymmetric, progressive, and adaptive coding techniques. On the theoretical front, the basic result shows that a random field (an ensemble of images) can be coded block by block such that the interblock redundancy can be completely removed while the individual blocks are transform coded. On the practical side, the artifact of tiling, a block boundary effect, present in conventional block by block transform coding techniques has been greatly suppressed. This book contains not only a theoretical discussion of the algorithms but also exhaustive simulation and suggested methodologies for ensemble design techniques. Each of the resulting algorithms has been applied to twelve images over a wide range of image data rates and the results are reported using subjective descriptions, photographs, mathematical MSE values, and h-plots, a recently proposed graphical representation showing a high level of agreement with image quality as judged subjectively.
Second-order Prediction and Residue Vector Quantization for Video Compression
Author: Bihong HuangPublisher:
ISBN:
Category :
Languages : en
Pages : 0
Book Description
Video compression has become a mandatory step in a wide range of digital video applications. Since the development of the block-based hybrid coding approach in the H.261/MPEG-2 standard, new coding standard was ratified every ten years and each new standard achieved approximately 50% bit rate reduction compared to its predecessor without sacrificing the picture quality. However, due to the ever-increasing bit rate required for the transmission of HD and Beyond-HD formats within a limited bandwidth, there is always a requirement to develop new video compression technologies which provide higher coding efficiency than the current HEVC video coding standard. In this thesis, we proposed three approaches to improve the intra coding efficiency of the HEVC standard by exploiting the correlation of intra prediction residue. A first approach based on the use of previously decoded residue shows that even though gains are theoretically possible, the extra cost of signaling could negate the benefit of residual prediction. A second approach based on Mode Dependent Vector Quantization (MDVQ) prior to the conventional transformed scalar quantization step provides significant coding gains. We show that this approach is realistic because the dictionaries are independent of QP and of a reasonable size. Finally, a third approach is developed to modify dictionaries gradually to adapt to the intra prediction residue. A substantial gain is provided by the adaptivity, especially when the video content is atypical, without increasing the decoding complexity. In the end we get a compromise of complexity and gain for a submission in standardization.
Video Image Compression Using Subband Coding and Vector Quantization
Author: Eric Kwok-Leong LoStructured 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.
Vector Quantization and Signal Compression
Author: Allen GershoPublisher: Springer Science & Business Media
ISBN: 146153626X
Category : Technology & Engineering
Languages : en
Pages : 737
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.
Digital Image Compression Techniques
Author: Majid RabbaniPublisher: SPIE-International Society for Optical Engineering
ISBN:
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.
Handbook of Image and Video Processing
Author: Alan C. BovikPublisher: Academic Press
ISBN: 0080533612
Category : Technology & Engineering
Languages : en
Pages : 1429
Book Description
55% new material in the latest edition of this "must-have for students and practitioners of image & video processing!This Handbook is intended to serve as the basic reference point on image and video processing, in the field, in the research laboratory, and in the classroom. Each chapter has been written by carefully selected, distinguished experts specializing in that topic and carefully reviewed by the Editor, Al Bovik, ensuring that the greatest depth of understanding be communicated to the reader. Coverage includes introductory, intermediate and advanced topics and as such, this book serves equally well as classroom textbook as reference resource. • Provides practicing engineers and students with a highly accessible resource for learning and using image/video processing theory and algorithms • Includes a new chapter on image processing education, which should prove invaluable for those developing or modifying their curricula • Covers the various image and video processing standards that exist and are emerging, driving today's explosive industry • Offers an understanding of what images are, how they are modeled, and gives an introduction to how they are perceived • Introduces the necessary, practical background to allow engineering students to acquire and process their own digital image or video data • Culminates with a diverse set of applications chapters, covered in sufficient depth to serve as extensible models to the reader's own potential applications About the Editor... Al Bovik is the Cullen Trust for Higher Education Endowed Professor at The University of Texas at Austin, where he is the Director of the Laboratory for Image and Video Engineering (LIVE). He has published over 400 technical articles in the general area of image and video processing and holds two U.S. patents. Dr. Bovik was Distinguished Lecturer of the IEEE Signal Processing Society (2000), received the IEEE Signal Processing Society Meritorious Service Award (1998), the IEEE Third Millennium Medal (2000), and twice was a two-time Honorable Mention winner of the international Pattern Recognition Society Award. He is a Fellow of the IEEE, was Editor-in-Chief, of the IEEE Transactions on Image Processing (1996-2002), has served on and continues to serve on many other professional boards and panels, and was the Founding General Chairman of the IEEE International Conference on Image Processing which was held in Austin, Texas in 1994.* No other resource for image and video processing contains the same breadth of up-to-date coverage* Each chapter written by one or several of the top experts working in that area* Includes all essential mathematics, techniques, and algorithms for every type of image and video processing used by electrical engineers, computer scientists, internet developers, bioengineers, and scientists in various, image-intensive disciplines
Visual Information Representation, Communication, and Image Processing
Author: Ya-Qin ZhangPublisher: CRC Press
ISBN: 9780824719289
Category : Computers
Languages : en
Pages : 584
Book Description
Discusses recent advances in the related technologies of multimedia computers, videophones, video-over-Internet, HDTV, digital satellite TV and interactive computer games. The text analyzes ways of achieving more effective navigation techniques, data management functions, and higher throughout networking. It synthesizes data on visual information venues, tracking the enormous commercial potential for new components and compatible systems.