Author: Simon LuceyPublisher:
ISBN:
Category : Image compression
Languages : en
Pages : 396
Book Description
Low-rate Image Compression Using Vector Quantization
Author: Simon LuceyPublisher:
ISBN:
Category : Image compression
Languages : en
Pages : 396
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.
Image Compression Using Vector Quantization
Author: Sharon Malka PerlmutterPublisher:
ISBN:
Category :
Languages : en
Pages : 366
Book Description
The Development of Algorithms for Variable Rate Vector Quantization in Image Compression
Author: George Beshara BendakPublisher:
ISBN:
Category : Computer algorithms
Languages : en
Pages : 168
Book Description
Novel Image Compression Methods Based on Vector Quantization
Author: M. Mary Shanthi RaniPublisher: LAP Lambert Academic Publishing
ISBN: 9783659662737
Category :
Languages : en
Pages : 188
Book Description
The rapid growth and development of electronic imaging in the recent years has led to large scale digital media archives. These are increasingly becoming popular as more and more digital media contents are created and deployed online every day. A critical issue in designing such archives is effective storage of the data. Uncompressed data requires more storage and huge bandwidth for transmission. Though the cost of storage is rapidly dropping, compression still remains as a challenging issue due to the growing number of multimedia based online applications. This necessitates the design of highly efficient image compression systems which promise good image quality and compression ratios with low computational complexity. This book is an outcome of the research in vector quantization based methods for compressing still images. It discusses novel image compression methods with performance analysis using standard compression metrics and their vital role in real-time applications. The proposed methods can be used in applications like Medical Image Processing, Mobile Applications, Biometrics, Remote Sensing and other online web applications.
Image Compression and Classification Using Vector Quantization
Author: Karen Louise OehlerStructured 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.
Color Image Compression Using Vector Quantization and Neural Networks
Author: Julio A. HernándezPublisher:
ISBN:
Category : Image compression
Languages : en
Pages : 126
Book Description
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.
Image Compression Using Vector Quantization and Lossless Index Coding
Author: Mark Dee HetheringtonPublisher:
ISBN:
Category :
Languages : en
Pages : 298
Book Description