BLOCK PERMUTATION CODING OF IMAGES USING COSINE TRANSFORM

We present the theory and practice of permutation coding as a new tool for very low-bit-rate image compression. Conventional source coding d eals with the data information of signals, while the permutation codin g achieves compression through efficiently representing the positional information (i.e., position permutation) caused by ordering the data information into order statistics. A set of four theorems is presented . The first one reveals the information-theoretic relationship between data and permutation information and the rest solves the efficient co ding problem. For this, novel tools from finite group theory are appli ed to derive a compact form of representation for permutation, called permutation-cyclic-reprsentation (PCR)-vectors, with which various reg ularities and constraints in the structure of positional information a re displayed, whereby the coding is made very easy using a runlength a nd Huffman method. A block DCT-based permutation coding algorithm (the BCPC) is developed attempting to combine DCT's excellent features of energy packing and magnitude ordering that are-found to be amenable to the permutation coding. This mutually benefitial characteristic signi ficantly reduces the coding bit-rate. Simulation results are provided for real images, showing an improvement by 3-4 dB in the peak-SNR inde x as compared to those representing the state-of-the-art.