Author: Yan Huat SimPublisher:
ISBN:
Category : Image processing
Languages : en
Pages : 192
Book Description
Subband Image Coding Using Vector Quantization
Author: Yan Huat SimPublisher:
ISBN:
Category : Image processing
Languages : en
Pages : 192
Book Description
Subband Image Coding
Author: John W. WoodsPublisher: Springer Science & Business Media
ISBN: 1475721196
Category : Technology & Engineering
Languages : en
Pages : 365
Book Description
This book concerns a new method of image data compression which weil may supplant the well-established block-transfonn methods that have been state-of-the art for the last 15 years. Subband image coding or SBC was first perfonned as such in 1985, and as the results became known at first through conference proceedings, and later through journal papers, the research community became excited about both the theoretical and practical aspects of this new approach. This excitement is continuing today, with many major research laboratories and research universities around the world investigating the subband approach to coding of color images, high resolution images, video- including video conferencing and advanced tele vision, and the medical application of picture archiving systems. Much of the fruits of this work is summarized in the eight chapters of this book which were written by leading practitioners in this field. The subband approach to image coding starts by passing the image through a two- or three-dimensional filter bank. The two-dimensional (2-D) case usually is hierarchical' consisting of two stages of four filters each. Thus the original image is split into 16 subband images, with each one decimated or subsampled by 4x4, resulting in a data conservation. The individual channel data is then quantized ·for digital transmission. In an attractive variation an octave-like approach, herein tenned subband pyramid, is taken for the decomposition resulting in a total of just eleven subbands.
Subband Image Coding with Vector Quantization
Author: Jonathan Nelson BradleyPublisher:
ISBN:
Category : Digital communications
Languages : en
Pages : 278
Book Description
Video Image Compression Using Subband Coding and Vector Quantization
Author: Eric Kwok-Leong LoVector Quantization in Subband Coding of Images
Author: Saad John BedrosLow Bit-rate Subband Coding of Image and Video Signals Using Vector Quantization
Author: Choon S. KimPublisher:
ISBN:
Category : Image processing
Languages : en
Pages : 214
Book Description
Subband Coding of Images Using Binomial QMF and Vector Quantization
Author: Kannan RajamaniPublisher:
ISBN:
Category : Image compression
Languages : en
Pages : 136
Book Description
Subband Coding of Images with Recursive Allpass Filters Using Vector Quantization
Author: Philippe JeanrenaudPublisher:
ISBN:
Category : Imaging systems
Languages : en
Pages : 126
Book Description
Subband-vector Quantization Coding of Color Images with Perceptually Optimal Bit Allocation
Author: Robert E. Van DyckVector 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.