High Dynamic Range Image Compression On Commodity Hardware For Real-Time Mapping Applications

Abstract

This paper describes a lossy compression scheme for high dynamic range graylevel and color imagery for data transmission purposes in real-time mapping scenarios. The five stages of the implemented non-standard transform coder are written in portable C++ code and do not require specialized hardware to run. Storage space occupied by the bitmaps is reduced via a color space change, 2D integer discrete cosine transform (DCT) approximation, coefficient quantization, two-size run-length encoding and dictionary matching hinged on the LZ4 algorithm. Quantization matrices to eliminate insignificant DCT coefficients are derived from a representative image set through genetic optimization. The underlying fitness function incorporates the obtained output size, classic image quality metrics and the unique color count. Together with a zone-based adaptation mechanism, this allows to specify target bitrates instead of percentage values or abstract quality factors for the reduction rate to be directly matched to the available communication channel capacities. Results on a camera control unit of a fixed-wing unmanned aircraft system built around entry-level PC hardware revealed single-thread compression and decompression throughputs of several hundred mebibytes per second for full-swing 16 and 32 bit RGB imagery at medium compression ratios. A degradation in image quality compared to popular compression libraries could be identified, however, at acceptable levels statistically and visually.