Rate-adaptive sub-band coding for high-fidelity compression of very high resolution images

Considering the development of an efficient coding technique for high-fidelity compression of very high resolution images, the authors first compare three different scalar quantization schemes and improved permutation codes from the aspect of quantization performance for a memory-less probability distribution that well approximates the real statistical properties of high frequency sub-band signals, and demonstrate that at low coding rates the improved permutation codes algorithm is the most suitable quantization scheme. Furthermore, the authors develop a rate-adaptive quantization technique that chooses the proper quantization scheme from among different types of quantization schemes according to the number of bits allocated to each subblock, and apply it to the high-fidelity encoding of sub-band signals. The results of simulations conducted on very high resolution images demonstrate that the proposed rate-adaptive quantization technique is very useful as a means for quantizing sub-band signals of very high resolution images