Browsing by Subject "Data compression (Telecommunication)"
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Item An optimized vector quantization for color image compression(Texas Tech University, 1998-05) Kompella, Sastry V SImage Data compression using vector quantization (VQ) has received a lot of attention in the recent years because of its optimality in rate distortion and adaptability. A fundamental goal of data compression is to reduce the bit rate for transmission or data storage while maintaining an acceptable fidelity or image quality. The combination of subband coding and vector quantization can provide a powerful method for compressing color images. Most of the existing VQ algorithms however suffer from a number of serious problems like long search process, codebook initialization, getting trapped in local minima, etc. This work investigates the development of an image compression algorithm using a variable block size vector quantization technique for generation of optimal codebook by employing a neuro-fuzzy clustering approach to ensure minimum distortion. Each color image is decomposed into R, G, and B color planes prior to application of wavelet transform and vector quantization to each color plane. Each color plane is preprocessed by performing multiresolution wavelet decomposition. The multiresolution nature of the discrete wavelet transform is utilized to decompose the images into more directionally decorrelated sub-images, which are more suitable for quantization and coding. Vector quantization is performed on each of the subimages at different resolutions and a multiresolution codebook scheme is utilized. This new approach to image compression facilitates generation of an improved globally optimal codebook, and a simpler search scheme. Finally, the codebooks generated from the three encoded color planes are entropy coded for obtaining higher compression at minimum distortion. Each color plane codebook is decoded and the reconstructed color planes are combined to form the final reconstructed image. The reconstructed images are compared with those of other standard compression algorithms, in terms of Mean square error (MSE), and Peak signal-to-noise ratio (PSNR).Item Bi-directional packing of compressed multimedia data for improved error resiliency(Texas Tech University, 2001-05) Srinivasan, AravindMost data compression schemes split the input signal into blocks and then produce a variable length code for each block. Since variable length codes are highly sensitive to channel errors that may occur during transmission, synchronization code words are often inserted between blocks to provide occasional resynchronization thereby adding more redundant bits of data. Error-resilient entropy coding (EREC) is a method of adapting existing schemes to give increased resilience to random and burst errors while maintaining high compression. This report proposes improvements to the EREC algorithm to increase its error resiliency. The objective is to pack code blocks in fixed-size slots, so that in the presence of bit errors, more data (blocks) can be recovered than is possible with the original EREC method of packing.Item Real-time lossless compression(Texas Tech University, 2000-12) Hargrave, James RogerThis thesis covers the selection and design of a lossless coding algorithm for optimal performance of high speed data transfer using a very large-scale integration (VLSI) of the algorithm on a dedicated chip for real time operation. The choice of the lossless coding algorithm is based on a comparative evaluation of the existing lossless coding algorithms, computational efficiency of parallel versus serial design and parameter optimization. Reduced multiplication arithmetic coding is found to be the best choice for efficient real time transmission of large data files at speeds exceeding one gigabit per second.Item Space frequency quantization in video compression(Texas Tech University, 2004-05) Pai, Sunil SubraoThe recent explosion in digital video storage and delivery has presented strong motivations for high performance video compression solutions. One second of uncompressed video would require about 30 MB of disk space (30 fps x 921,600 bytes per frame). For today's PCs, 10 MBs per second data throughput rates is considered fast. With the web, we have an even more significant problem. With the current storage devices and the bandwidth available, the only way to share videos is to compress them, and higher the compression the better it is. Over the past decade, the wavelets have been used successfully in solving many difficult problems requiring transform domain processing, including image compression (e.g., JPEG 2000). This thesis is an attempt to use wavelet transform in video compression instead of the traditional discrete cosine transform (DCT)-based technique.