Making the Best of JPEG at Very High Compression Ratios: Rectangular Pixel Averaging for Mars PathFi

Abstract

As more and more NASA missions are turning to image compression to maximize their data return at constrained bit rates, and very often adopting JPEG as the centerpiece of their image compression system, they are noticing one limitation of JPEG: its poor performance at very high compression ratios (typically 32 and above). This is the case for engineering uses of image data on Mars Pathfinder such as assessment of lander condition and deployed airbags, and rover navigation. Unlike science scenes, images for engineering at low resolution are often sufficient. Unfortunately, at very high compression ratios, JPEG produces unacceptable artifacts, due to the limitation of the size of the Discrete Cosine Transform to 8, for which no clever quantization or entropy coding can compensate. Still, JPEG can successfully be used as part of a compression scheme if the encoding is preceeded by low-pass filtering and downsampling, while the decoding is followed by interpolation and upsampling, to restore the image to its original size. The choice for the horizontal and vertical downsampling/upsampling factors is made based on the known distance to the objective and its size, as well as on the fact that resolution in azimuth degrades more gradually than in elevation, leading to a larger downsampling factor in azimuth. Assuming unweighted pixel averaging is used as the low-pass filter before decimation, optimal interpolation filters which minimize the mean squared reconstruction error (MSRE) in the absence of JPEG are derived. In the presence of large JPEG-induced quantization noise however, bilinear interpolation filters are shown to outperform the optimal interpolation filters derived above. Engineering assessment of images compressed with this scheme at ratios up to 126-to-1 using bilinear interpolation confirm its performance and its success in extending the operational compression ratio range of JPEG.