An Investigation of Vector Quantization Based Methods for Image Compression PDF Download

Author: Amit A. Mahadik
Publisher:
ISBN:
Category : Image processing
Languages : en
Pages : 115

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Author: M. Mary Shanthi Rani
Publisher: LAP Lambert Academic Publishing
ISBN: 9783659662737
Category :
Languages : en
Pages : 188

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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.

Author: Zhongxiu Wen
Publisher:
ISBN:
Category : Data compression (Telecommunication)
Languages : en
Pages : 156

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Vector quantization (VQ) is an effective spatial domain image compression technique which maps discrete k-dimensional vectors into a digital sequence suitable for communication or storage. This research investigates methods for improving the performance of vector quantization based on pyramid tools. An iterative optimization clustering VQ procedure based upon an initial codebook randomly sampled from the training set is presented. The main idea of the proposed algorithm is that a set of new cluster means is generated by using an iterative clustering algorithm, with the previous codewords as seeds. The training set is drawn from the present training images. The resulting cluster means are then used in a new codebook which is continually refined so that each iteration reduces the distortion involved in coding a given training set. The goal of such system is to reduce the bit rate so as to minimize communication channel capacity or digital storage memory requirement. This VQ can provide a reduction from 8 bits per pixel (bpp) to 2 bpp or 0.5 bpp with negligible degradation image quality. Vector quantization usually requires extensive computations. In this thesis both the pyramid processing and the fast algorithms are examined for vector quantization. After a brief introduction of the topic in Chapter 1, the history and fundamentals of vector quantization are presented in Chapter 2. Chapter 3 describes the concepts and techniques of pyramid image processing. A new VQ algorithm which is employed in the thesis is examined in Chapter 4. In Chapter 5 the importance of post-processing is emphasized with illustrative results. Even with post-processing the vector quantization method considered indeed provides a significantly better image compression over existing image compression technique.

Author: Allen Gersho
Publisher: Springer Science & Business Media
ISBN: 0792391810
Category : Technology & Engineering
Languages : en
Pages : 762

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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.

Author: Colin Scott Ramsay
Publisher:
ISBN:
Category : Image compression
Languages : en
Pages :

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Author: Xin-She Yang
Publisher: Luniver Press
ISBN: 1905986289
Category : Computers
Languages : en
Pages : 148

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Modern metaheuristic algorithms such as bee algorithms and harmony search start to demonstrate their power in dealing with tough optimization problems and even NP-hard problems. This book reviews and introduces the state-of-the-art nature-inspired metaheuristic algorithms in optimization, including genetic algorithms, bee algorithms, particle swarm optimization, simulated annealing, ant colony optimization, harmony search, and firefly algorithms. We also briefly introduce the photosynthetic algorithm, the enzyme algorithm, and Tabu search. Worked examples with implementation have been used to show how each algorithm works. This book is thus an ideal textbook for an undergraduate and/or graduate course. As some of the algorithms such as the harmony search and firefly algorithms are at the forefront of current research, this book can also serve as a reference book for researchers.

Author: Madhuri A. Joshi
Publisher: CRC Press
ISBN: 1482228238
Category : Computers
Languages : en
Pages : 228

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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

Author: Manijeh Khataie
Publisher:
ISBN:
Category : Data compression (Telecommunication)
Languages : en
Pages : 0

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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.

Author:
Publisher:
ISBN:
Category :
Languages : en
Pages : 0

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In the research conducted under this grant, we addressed the problem of transmitting images compressed with high quality wavelet compression algorithms over packet erasure networks, multiple description channels, and noisy communication channels. In addition, we developed new methods for wavelet image compression based on group testing; developed a variation of the set partitioning in hierarchical trees algorithm; and developed a method for fast search of an entropy-constrained vector quantization codebook.

Author: Sanjay Mishra
Publisher:
ISBN:
Category : Data compression (Computer science)
Languages : en
Pages : 240

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