Logic Minimization Based Approach for Compressing Image Data

摘要

We propose a novel approach for the lossless compression of binary images using logic minimization. The image is divided into windows or blocks of size $rimes c$ pixels and each block is transformed into a Boolean switching function in cubical form, treating the pixel values as output of the function. Compression is performed by minimizing these switching functions using ESPRESSO, a cube-based two-level logic minimizer. To reduce the bits required to encode the minimized cubes (product terms), a code set which satisfies the prefix property is used. If this technique fails to produce compression for a window, the pixels are stored as such. The main motivation of the work has been to investigate the potential of logic minimization as a tool for image data compression. Our technique outperforms UNIX compress in terms of compression ratio on most of the test images. The compression scheme is relatively slower while the decompression time is comparable to that of UNIX compress.