Achieving equal image quality at lower bit rates using evolved image reconstruction transforms

摘要

Several recent NASA missions have used the state-of-the-art wavelet-based ICER Progressive Image Compressor for lossy image compression. In this paper, we describe a methodology for using evolutionary computation to optimize wavelet and scaling numbers describing reconstruction-only multiresolution analysis (MRA) transforms that are capable of accepting as input test images compressed by ICER software at a reduced bit rate (e.g., 0.99 bits per pixel [bpp]), and producing as output images whose average quality, in terms of mean squared error (MSE), equals that of images produced by ICER's reconstruction transform when applied to the same test images compressed at a higher bit rate (e.g., 1.00 bpp). This improvement can be attained without modification to ICER's compression, quantization, encoding, decoding, or dequantization algorithms, and with very small modifications to existing ICER reconstruction filter code. As a result, future NASA missions will be able to transmit greater amounts of information (i.e., a greater number of images) over channels with equal bandwidth, thus achieving a no-cost improvement in the science value of those missions.