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Author: Alper Erdemir Publisher: ISBN: Category : Languages : en Pages : 74
Book Description
This thesis proposes a new analysis/synthesis procedure for speech and image compression. The algorithm applies the discrete wavelet transform to subject data in order to obtain a set of multiresolution wavelet coefficients. The wavelet coefficients are then encoded by using the generalized Lloyd algorithm. The statistical properties of the wavelet coefficients are utilized to determine the number of resolution levels as well as the codebook size at each resolution level. Coding results show that the new procedure provides a significant improvement in the quality of the reproduced data. The tested data includes speech, image, and transient signals.
Author: Alper Erdemir Publisher: ISBN: Category : Languages : en Pages : 74
Book Description
This thesis proposes a new analysis/synthesis procedure for speech and image compression. The algorithm applies the discrete wavelet transform to subject data in order to obtain a set of multiresolution wavelet coefficients. The wavelet coefficients are then encoded by using the generalized Lloyd algorithm. The statistical properties of the wavelet coefficients are utilized to determine the number of resolution levels as well as the codebook size at each resolution level. Coding results show that the new procedure provides a significant improvement in the quality of the reproduced data. The tested data includes speech, image, and transient signals.
Author: Alper Erdemir Publisher: ISBN: Category : Languages : en Pages : 0
Book Description
This thesis proposes a new analysis/synthesis procedure for speech and image compression. The algorithm applies the discrete wavelet transform to subject data in order to obtain a set of multiresolution wavelet coefficients. The wavelet coefficients are then encoded by using the generalized Lloyd algorithm. The statistical properties of the wavelet coefficients are utilized to determine the number of resolution levels as well as the codebook size at each resolution level. Coding results show that the new procedure provides a significant improvement in the quality of the reproduced data. The tested data includes speech, image, and transient signals.
Author: Pankaj N. Topiwala Publisher: Springer Science & Business Media ISBN: 0306470438 Category : Science Languages : en Pages : 434
Book Description
An exciting new development has taken place in the digital era that has captured the imagination and talent of researchers around the globe - wavelet image compression. This technology has deep roots in theories of vision, and promises performance improvements over all other compression methods, such as those based on Fourier transforms, vectors quantizers, fractals, neural nets, and many others. It is this revolutionary new technology that is presented in Wavelet Image and Video Compression, in a form that is accessible to the largest audience possible. Wavelet Image and Video Compression is divided into four parts. Part I, Background Material, introduces the basic mathematical structures that underly image compression algorithms with the intention of providing an easy introduction to the mathematical concepts that are prerequisites for the remainder of the book. It explains such topics as change of bases, scalar and vector quantization, bit allocation and rate-distortion theory, entropy coding, the discrete-cosine transform, wavelet filters and other related topics. Part II, Still Image Coding, presents a spectrum of wavelet still image coding techniques. Part III, Special Topics in Still Image Coding, provides a variety of example coding schemes with a special flavor in either approach or application domain. Part IV, Video Coding, examines wavelet and pyramidal coding techniques for video data. Wavelet Image and Video Compression serves as an excellent reference and may be used as a text for advanced courses covering the subject.
Author: Inderpreet Singh Publisher: ISBN: Category : Languages : en Pages :
Book Description
With the evolution of multimedia systems, image and video compression is becoming the key enabling technology for delivering various image/video services over heterogeneous networks. The basic goal of image data compression is to reduce the bit rate for transmission and storage while either maintaining the original quality of the data or providing an acceptable quality. This thesis proposes a new wavelet transform for lossless compression of images with application to medical images. The transform uses integer arithmetic and is very computationally efficient. Then a new color image transformation, which is reversible and uses integer arithmetic, is proposed. The transformation reduces the redundancy among the red, green, and blue color bands. It approximates the luminance and chrominance components of the YIQ coordinate system. This transformation involves no floating point/integer multiplications or divisions, and is, therefore, very suitable for real-time applications where the number of CPU cycles needs to be kept to a minimum. A technique for lossy compression of an image data base is also proposed. The technique uses a wavelet transform and vector quantization for compression. The discrete cosine transform is applied to the coarsest scale wavelet coefficients to achieve even higher compression ratios without any significant increase in computational complexity. Wavelet denoising is used to reduce the image artifacts generated by quantizing the discrete cosine transform coefficients. This improves the subjective quality of the decompressed images for very low bit rate images (less than 0.5 bits per pixel). The thesis also deals with the real-time implementation of the wavelet transform. The new wavelet transform has been applied to speech signals. Both lossless and lossy techniques for speech coding have been implemented. The lossless technique involves using the reversible integer-arithmetic wavelet transform and Huffman coding to obtain the compressed bitstream. The lossy technique, on the other hand, quantizes the wavelet coefficients to obtain higher compression ratio at the expense of some degradation in sound quality. The issues related to real-time wavelet compression are also discussed. Due to the limited size of memory on a DSP, a wavelet transform had to be applied to an input signal of finite length. The effects of varying the signal length on compression performance are also studied for different reversible wavelet transforms. The limitations of the proposed techniques are discussed and recommendations for future research are provided.
Author: Allen Gersho Publisher: 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.
Author: Kanidta Positwinyu Publisher: ISBN: 9789743338090 Category : Image compression Languages : en Pages : 128
Book Description
Image processing requires an enormous storage, processing, and communication. To reduce this amount of data, image compression is necessary. We applied wavelet transform, which is an up coming technique and very powerful tools for signal processing, to color image compression. In this thesis, we use Daubechies 20 wavelet transform to the image compression procedure. There are five steps in the procedure. First, we extract color image into RGB components. Second, we transform RGB components to wavelet coefficients by using wavelet transform and pyramid algorithm. Third, we cut off some coefficients and scaled the results to eliminate less important data. Forth, we quantize wavelet coefficients by LBG vector quantization according to the significant of wavelet coefficients. Finally, we apply arithmetic coding, which is a lossless coding process, to wavelet coefficients. We test our algorithm with the images of Lena and Peppers. Lena is compressed with compression ratio 50-60 yielding PSNR around 34-35 and compression ratio 80-100 yielding PSNR around 30-31. Peppers is compressed with compression ratio 55-58 yielding PSNR around 34 and compression ratio 80-100 yielding PSNR around 30. Comparing with JPEG, this technique gives high PSNR than JPEG, at high compression ratio or compression ratio over 90, but less PSNR at low compression ratio or compression ratio below 85.
Author: Kamisetty Ramam Rao Publisher: CRC Press ISBN: 1420037382 Category : Computers Languages : en Pages : 408
Book Description
Data compression is one of the main contributing factors in the explosive growth in information technology. Without it, a number of consumer and commercial products, such as DVD, videophone, digital camera, MP3, video-streaming and wireless PCS, would have been virtually impossible. Transforming the data to a frequency or other domain enables even more efficient compression. By illustrating this intimate link, The Transform and Data Compression Handbook serves as a much-needed handbook for a wide range of researchers and engineers. The authors describe various discrete transforms and their applications in different disciplines. They cover techniques, such as adaptive quantization and entropy coding, that result in significant reduction in bit rates when applied to the transform coefficients. With clear and concise presentations of the ideas and concepts, as well as detailed descriptions of the algorithms, the authors provide important insight into the applications and their limitations. Data compression is an essential step towards the efficient storage and transmission of information. The Transform and Data Compression Handbook provides a wealth of information regarding different discrete transforms and demonstrates their power and practicality in data compression.
Author: Stephen T. Welstead Publisher: SPIE Press ISBN: 9780819435033 Category : Technology & Engineering Languages : en Pages : 264
Book Description
Interest in image compression for internet and other multimedia applications has spurred research into compression techniques that will increase storage capabilities and transmission speed. This tutorial provides a practical guide to fractal and wavelet approaches--two techniques with exciting potential. It is intended for scientists, engineers, researchers, and students. It provides both introductory information and implementation details. Three Windows-compatible software systems are included so that readers can explore the new technologies in depth. Complete C/C++ source code is provided, enabling readers to go beyond the accompanying software. The mathematical presentation is accessible to advanced undergraduate or beginning graduate students in technical fields.
Author: Alper Erdemir
Author: Alper Erdemir
Author: Alper Erdemir
Author: Pankaj N. Topiwala
Author: Inderpreet Singh
Author: Allen Gersho
Author: Kanidta Positwinyu
Author: Ioannis Katsavounidis
Author: Kamisetty Ramam Rao
Author: Stephen T. Welstead
Author: Anthony T. Pollock