An Optimized Vector Quantization for Color Image Compression PDF Download

Author: Sastry V. S. Kompella
Publisher:
ISBN:
Category : Coding theory
Languages : en
Pages : 110

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Book Description

Author: Shuyu Yang
Publisher:
ISBN:
Category : Fuzzy algorithms
Languages : en
Pages : 110

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Book Description

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

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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.

Author: Gloria Yu-Fen Yang
Publisher:
ISBN:
Category :
Languages : en
Pages : 130

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Book Description

Author: Julio A. Hernández
Publisher:
ISBN:
Category : Image compression
Languages : en
Pages : 126

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Book Description

Author: Jude Hemanth
Publisher: Springer
ISBN: 3319960024
Category : Technology & Engineering
Languages : en
Pages : 305

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Book Description
This book provides a platform for exploring nature-inspired optimization techniques in the context of imaging applications. Optimization has become part and parcel of all computational vision applications, and since the amount of data used in these applications is vast, the need for optimization techniques has increased exponentially. These accuracy and complexity are a major area of concern when it comes to practical applications. However, these optimization techniques have not yet been fully explored in the context of imaging applications. By presenting interdisciplinary concepts, ranging from optimization to image processing, the book appeals to a broad readership, while also encouraging budding engineers to pursue and employ innovative nature-inspired techniques for image processing applications.

Author: James Melvin Crissey
Publisher:
ISBN:
Category : Data compression (Computer science)
Languages : en
Pages : 418

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Book Description

Author: Richard Jaramillo
Publisher:
ISBN:
Category : Genetic programming (Computer science)
Languages : en
Pages : 212

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Book Description
The optimization of lossy compression of images is inherently difficult due to the complexity of human visual perception. Existing optimization techniques perform adequately, but often stop at local optimal points in the search space of compression solutions. Evolutionary programming is an alternative to human-designed algorithms that has been applied successfully to overcome local optima in machine learning applications. Evolutionary programming borrows from nature the concepts of survival-of-the-fittest and the crossover of genetic material between individuals in a population to produce a new generation of individuals. The result is a guided search through the solution space for a problem. Genetic algorithms (GA) and genetic programming (GP) are two types of evolutionary programming. GA has been applied to many applications including vector quantization (VQ) compression codebook generation. GP is an extension of genetic algorithms in which the individuals in the evolving population are represented by hierarchically structured program trees instead of fixed length strings of characters. GP has been applied in various fields such as analog circuit design with results that rival human designed solutions to the same problems. No previous research has been found that applies GP to the problem of VQ codebook generation. Co-evolution is an extension of GP in which a population of problems to be solved evolves at the same time as the solution population evolves. Co-evolution has been shown to perform better than normal evolution at overcoming local optima for some applications. This research examines a novel use of genetic programming and coevolutionary genetic programming for the evolution and co-evolution of VQ codebooks for image compression. The results show that codebooks generated using traditional human-coded compression algorithms can be further optimized with the use of GP and co-evolutionary GP.

Author: S J Pise
Publisher: Springer Science & Business Media
ISBN: 8184899890
Category : Computers
Languages : en
Pages : 333

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Book Description
This proceedings is a representation of decades of reasearch, teaching and application in the field. Image Processing, Fusion and Information Technology areas, Digital radio Communication, Wimax, Electrical engg, VLSI approach to processor design, embedded systems design are dealt in detail through models and illustrative techniques.

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

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Book Description
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.