A Novel Approach to Design and Simulation of SPIHT Image Compression
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Recently, Image Compression is major concern in the field of Image processing. Lossy Image Compression is required to decrease the storage requirement and better data transfer rate. One of the best Image Compression technique is Wavelet Transform. Wavelet Transform uses a large variety of wavelets for decomposition of images. The state of the art coding techniques like EZW (Embedded Zero tree Wavelet), SPIHT (Set Partitioning In Hierarchical Trees) and WDR (Wavelet Difference Reduction) use the wavelet transform as basic. In my thesis I have used Discrete Wavelet Transform to improve the quali...
Recently, Image Compression is major concern in the field of Image processing. Lossy Image Compression is required to decrease the storage requirement and better data transfer rate. One of the best Image Compression technique is Wavelet Transform. Wavelet Transform uses a large variety of wavelets for decomposition of images. The state of the art coding techniques like EZW (Embedded Zero tree Wavelet), SPIHT (Set Partitioning In Hierarchical Trees) and WDR (Wavelet Difference Reduction) use the wavelet transform as basic. In my thesis I have used Discrete Wavelet Transform to improve the quality of the image with high PSNR(Peak Signal to Noise Ratio) value and the best compression ratio on the variety of images with the different sizes. The analysis has been carried out in terms of PSNR, CR (Compression Ratio) obtained and time taken for decomposition and reconstruction. The results have proved that the not only the PSNR value and CR achieved at very high rate but also the execution time taken by MSPIHT(Modified Set Partitioning In Hierarchical Trees) is very less as compared to other techniques.
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