2 research outputs found

    A New Case for Image Compression Using Logic Function Minimization

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    Lossless Compression of Images Using Logic Minimization

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    A novel approach for the lossless compression of images is presented. After preprocessing, the image is split into bit planes which are then divided into smaller blocks. Mixed blocks are converted to Boolean switching functions and then subjected to minimization to arrive at a compact representation, leading to possible data compression. Blocks are then classified into distinct events based on the outcome of logic minimization. A Huff-man code is constructed and the blocks are encoded suitably. This approach provides a framework to incorporate various possible switching theoretic techniques into the basic coding scheme proposed by us. This paper also shows that logic minimization can be used to handle blocks of larger size, than practically possible with Huffman coding, to yield significant compression on gray-level images. Our approach compares well with JPEG in terms of compression ratio
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