No description available.

Methods for digital image compression have been the subject of much study over the past decade. Advances in wavelet transforms and quantization methods have produced algorithms capable of surpassing the existing image compression standards like the Joint Photographic Experts Group (JPEG) algorithm. For best performance in image compression, wavelet transforms require filters that combine a number of desirable properties, such as orthogonality and symmetry. However, the design possibilities for wavelets are limited because they cannot simultaneously possess all of these desirable properties. The relatively new field of multiwavelets shows promise in removing some of the limitations of wavelets. Multiwavelets offer more design options and hence can combine all desirable transform features. The few previously published results of multiwavelet-based image compression have mostly fallen short of the performance enjoyed by the current wavelet algorithms. This thesis presents new multiwavelet transform methods and measurements that verify the potential benefits of multiwavelets. Using a zerotree quantization scheme modified to better match the unique decomposition properties of multiwavelets, it is shown that the latest multiwavelet filters can give performance equal to, or in many cases superior to, the current wavelet filters. The performance of multiwavelet packets is also explored for the first time and is shown to be competitive to that of wavelet packets in some cases. The wavelet and multiwavelet filter banks are tested on a much wider range of images than in the usual literature, providing a better analysis of the benefits and drawbacks of each. NOTE: (03/2007) An updated copy of this ETD was added after there were patron reports of problems with the file. / Master of Science

The success of any transform coding technique depends on how well the basis functions represent the signal features. The discrete wavelet transform (DWT) performs a multiresolution analysis of a signal; this enables an efficient representation of smooth and detailed signal regions. Furthermore, computationally efficient algorithms exist for computing the DWT. For these reasons, recent image compression standards such as JPEG2000 use the wavelet transform. It is well known that orthogonality and symmetry are desirable transform properties in image compression applications. It is also known that the scalar wavelet transform does not possess both properties simultaneously. Multiwavelets overcome this limitation; the multiwavelet transform allows orthogonality and symmetry to co-exist. However recently reported image compression results indicate that the scalar wavelets still outperform the multiwavelets in terms of peak signal-to-noise ratio (PSNR). In a multiwavelet transform, the balancing order of the multiwavelet is indicative of its energy compaction efficiency (usually a higher balancing order implies lower mean-squared-error, MSE, in the compressed image). But a high balancing order alone does not ensure good image compression performance. Filter bank characteristics such as shift-variance, magnitude response, symmetry and phase response are important factors that also influence the MSE and perceived image quality. This thesis analyzes the impact of these multiwavelet characteristics on image compression performance. Our analysis allows us to explain---for the first time---reasons for the small performance gap between the scalar wavelets and multiwavelets. We study the characteristics of five balanced multiwavelets (and 2 unbalanced multiwavelets) and compare their image compression performance for grayscale images with the popular (9,7)-tap and (22,14)-tap biorthogonal scalar wavelets. We use the well-known SPIHT quantizer in our compression scheme and utilize PSNR and subjective quality measures to assess performance. We also study the effect of incorporating a human visual system (HVS)-based transform model in our multiwavelet compression scheme. Our results indicate those multiwavelet properties that are most important to image compression. Moreover, the PSNR and subjective quality results depict similar performance for the best scalar wavelets and multiwavelets. Our analysis also shows that the HVS-based multiwavelet transform coder considerably improves perceived image quality at low bit rates. / Master of Science

No description available.

No description available.

The last few decades have witnessed what is commonly known as an "information explosion". The advent of the Internet has enabled the sharing of large amounts of information between users in almost every part of the world. This had led to increased bandwidth and storage requirements. These requirements necessitate the development of new techniques to optimize the utilization of existing bandwidth and to minimize storage requirements. In emerging areas of real-time multimedia applications, researchers have successfully developed new approaches, employing techniques such as transform coding, prediction, vector quantization, etc, to efficiently represent and consequently compress data, especially image data. Recently, multiple transform domain representation techniques have been reported which successfully compress one and multidimensional signals. In this thesis, a novel and efficient codec using multiple transform domain representation in conjunction with split vector quantization is presented, which provides superior coding performance for images. An adaptive scheme that further enhances the representation accuracy of the above codec is also described. Results of simulations of the proposed technique are presented that confirm the improved performance of the codec.

In this work, we propose the application fractal compression techniques to textured images segmentation, and use the transformation coefficients as features for segmentation. The result is improved by combining fractal dimension feature and the transformation coefficients from the original and its filter versions. Feature vectors are clustered together using K-mean algorithm with features pre-smoothing. The numbers of feature are minimized to reach the compromise result. In the integrated approach, we attempt to improve segmentation of texture images using our method. Background knowledge of image segmentation and image compression will be presented. Algorithms for fractal dimension calculation, K-means clustering, and fractal compression is given. Experimental results are included, and possible future work is mentioned.

Telepathology is defined as the practice of pathology at a distance using video imaging and telecommunications. In this thesis we address the two main technology challenges in implementing telepathology, viz. compression and transmission of digital pathology images. One of the barriers to telepathology is the availability and the affordability of high bandwidth communication resources. High bandwidth links are required because of the large size of the uncompressed digital pathology images. For efficient utilization of available bandwidth, these images need to be compressed. However aggressive image compression may introduce objectionable artifacts and result in an inaccurate diagnosis. This discussion helps us to identify two main design challenges in implementing telepathology, 1. Compression: There is a need to develop or select an appropriate image compression algorithm and an image quality criterion to ensure maximum possible image compression, while ensuring that diagnostic accuracy is not compromised. 2. Transmission: There is a need to develop or select a smart image transmission scheme which can facilitate the transmission of the compressed image to the remote pathologist without violating the specified bandwidth and delay constraints. We addressed the image compression problem by conducting subjective tests to determine the maximum compression that can be tolerated before the pathology images lose their diagnostic value. We concluded that the diagnostically lossless compression ratio is at least around 5 to 10 times higher than the mathematically lossless compression ratio, which is only about 2:1. We also set up subjective tests to compare the performance of the JPEG and the JPEG 2000 compression algorithms which are commonly used for compression of medical images. We concluded that JPEG 2000 outperforms JPEG at lower bitrates (bits/pixel), but both the algorithms perform equally well at higher bitrates. We also addressed the issue of image transmission for telepathology by proposing a two-stage transmission scheme, where coarse image information compressed at diagnostically lossless level is sent to the clients at the first stage, and the Region of Interest is transmitted at mathematically lossless compression levels at the second stage, thereby reducing the total image transmission delay.

Esta dissertação apresenta o desenvolvimento de arquiteturas para a compressão JPEG, onde são apresentadas arquiteturas de um compressor JPEG para imagens em tons de cinza, de um compressor JPEG para imagens coloridas e de um conversor de espaço de cores de RGB para YCbCr. As arquiteturas desenvolvidas são detalhadamente apresentadas, tendo sido completamente descritas em VHDL, com sua síntese direcionada para FPGAs da família Flex10KE da Altera. A arquitetura integrada do compressor JPEG para imagens em tons de cinza possui uma latência mínima de 237 ciclos de clock e processa uma imagem de 640x480 pixels em 18,5ms, permitindo uma taxa de processamento de 54 imagens por segundo. As estimativas realizadas em torno da taxa de compressão obtida indicam que ela seria de aproximadamente 6,2 vezes ou de 84 %. A arquitetura integrada do compressor JPEG para imagens coloridas foi gerada a partir de adaptações na arquitetura do compressor para imagens em tons de cinza. Esta arquitetura também possui a latência mínima de 237 ciclos de clock, sendo capaz de processar uma imagem coloria de 640 x 480 pixels em 54,4ms, permitindo uma taxa de processamento de 18,4 imagens por segundo. A taxa de compressão obtida, segundo estimativas, seria de aproximadamente 14,4 vezes ou de 93 %. A arquitetura para o conversor de espaço de cores de RBG para YCbCr possui uma latência de 6 ciclos de clock e é capaz de processar uma imagem colorida de 640x480 pixels em 84,6ms, o que permite uma taxa de processamento de 11,8 imagens por segundo. Esta arquitetura não chegou a ser integrada com a arquitetura do compressor de imagens coloridas, mas algumas sugestões e estimativas foram realizadas nesta direção. / This dissertation presents the design of architectures for JPEG image compression. Architectures for a gray scale images JPEG compressor that were developed are herein presented. This work also addresses a color images JPEG compressor and a color space converter. The designed architectures are described in detail and they were completely described in VHDL, with synthesis directed for Altera Flex10KE family of FPGAs. The integrated architecture for gray scale images JPEG compressor has a minimum latency of 237 clock cycles and it processes an image of 640x480 pixels in 18,5ms, allowing a processing rate of 54 images per second. The compression rate, according to estimates, would be of 6,2 times or 84%, in percentage of bits compression. The integrated architecture for color images JPEG compression was generated starting from incremental changes in the architecture of gray scale images compressor. This architecture also has the minimum latency of 237 clock cycles and it can process a color image of 640 x 480 pixels in 54,4ms, allowing a processing rate of 18,4 images per second. The compression rate, according to estimates, would be of 14,4 times or 93%, in percentage of bits compression. The architecture for space color conversor from RBG to YCbCr has a latency of 6 clock cycles and it is able to process a color image of 640 x 480 pixels in 84,6ms, allowing a processing rate of 11,8 images per second. This architecture was finally not integrated with the color images compressor architecture, but some suggestions, alternatives and estimates were made in this direction.

Esta dissertação apresenta o desenvolvimento de arquiteturas para a compressão JPEG, onde são apresentadas arquiteturas de um compressor JPEG para imagens em tons de cinza, de um compressor JPEG para imagens coloridas e de um conversor de espaço de cores de RGB para YCbCr. As arquiteturas desenvolvidas são detalhadamente apresentadas, tendo sido completamente descritas em VHDL, com sua síntese direcionada para FPGAs da família Flex10KE da Altera. A arquitetura integrada do compressor JPEG para imagens em tons de cinza possui uma latência mínima de 237 ciclos de clock e processa uma imagem de 640x480 pixels em 18,5ms, permitindo uma taxa de processamento de 54 imagens por segundo. As estimativas realizadas em torno da taxa de compressão obtida indicam que ela seria de aproximadamente 6,2 vezes ou de 84 %. A arquitetura integrada do compressor JPEG para imagens coloridas foi gerada a partir de adaptações na arquitetura do compressor para imagens em tons de cinza. Esta arquitetura também possui a latência mínima de 237 ciclos de clock, sendo capaz de processar uma imagem coloria de 640 x 480 pixels em 54,4ms, permitindo uma taxa de processamento de 18,4 imagens por segundo. A taxa de compressão obtida, segundo estimativas, seria de aproximadamente 14,4 vezes ou de 93 %. A arquitetura para o conversor de espaço de cores de RBG para YCbCr possui uma latência de 6 ciclos de clock e é capaz de processar uma imagem colorida de 640x480 pixels em 84,6ms, o que permite uma taxa de processamento de 11,8 imagens por segundo. Esta arquitetura não chegou a ser integrada com a arquitetura do compressor de imagens coloridas, mas algumas sugestões e estimativas foram realizadas nesta direção. / This dissertation presents the design of architectures for JPEG image compression. Architectures for a gray scale images JPEG compressor that were developed are herein presented. This work also addresses a color images JPEG compressor and a color space converter. The designed architectures are described in detail and they were completely described in VHDL, with synthesis directed for Altera Flex10KE family of FPGAs. The integrated architecture for gray scale images JPEG compressor has a minimum latency of 237 clock cycles and it processes an image of 640x480 pixels in 18,5ms, allowing a processing rate of 54 images per second. The compression rate, according to estimates, would be of 6,2 times or 84%, in percentage of bits compression. The integrated architecture for color images JPEG compression was generated starting from incremental changes in the architecture of gray scale images compressor. This architecture also has the minimum latency of 237 clock cycles and it can process a color image of 640 x 480 pixels in 54,4ms, allowing a processing rate of 18,4 images per second. The compression rate, according to estimates, would be of 14,4 times or 93%, in percentage of bits compression. The architecture for space color conversor from RBG to YCbCr has a latency of 6 clock cycles and it is able to process a color image of 640 x 480 pixels in 84,6ms, allowing a processing rate of 11,8 images per second. This architecture was finally not integrated with the color images compressor architecture, but some suggestions, alternatives and estimates were made in this direction.