Logic minimization based approach for compressing image data

We propose a novel approach for the lofsless compression of binary images using logic minimization. The image is divided into windows or blocks of size r x 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 b y 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 f o r image d a t a 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 t ime is comparable to that of UNIX compress.