Development of Image Compression Algorithms: Using Soft Computing Techniques,Used

Development of Image Compression Algorithms: Using Soft Computing Techniques,Used

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Applications, which need to store large database and/or transmit digital images requiring high bitrates over channels with limited bandwidth, have demanded improved image compression techniques.. Encoding an image into fewer bits is useful in reducing the storage requirements in image archival systems, or in decreasing the bandwidth for image transmission. In standard image compression methods (e.g. JPEG), as the bits per pixel reduces, the picture quality deteriorates because of the use of bigger quantization step size. In this work, image compression techniques are designed keeping in mind the human visual system. Practical and effective image compression system based on NeuroWavelet models have been proposed which combines the advantages of neural network and wavelet transform with vector quantization. Fuzzy cmeans and Fuzzy vector quantization algorithms have also been used to make use of uncertainty for the benefit of the clustering process. We have compared the performances of different clustering algorithms applied to the proposed encoder. Experimental results on real images of varying complexity have established the robustness and effectiveness of the method

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To facilitate a smooth return process, a Return Authorization (RA) Number is required for all returns. Returns without a valid RA number will be declined and may incur additional fees. You can request an RA number within 15 days of the original delivery date. For more details, please refer to our Return & Refund Policy page.

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We provide a 2-year limited warranty, from the date of purchase for all our products.

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This warranty strictly does not cover damages that arose from negligence, misuse, wear and tear, or not in accordance with product instructions (dropping the product, etc.).

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