Compression Algorithm Selection for Multispectral Mastcam Images

The two mast cameras (Mastcam) onboard the Mars rover, Curiosity, are multispectral imagers with nine bands in each camera. Currently, the images are compressed losslessly using JPEG, which can achieve only two to three times compression. We present a two-step approach to compressing multispectral Mastcam images. First, we propose to apply principal component analysis (PCA) to compress the nine bands into three or six bands. This step optimally compresses the 9-band images through spectral correlation between the bands. Second, several well-known image compression codecs, such as JPEG, JPEG-2000 (J2K), X264, and X265, in the literature are applied to compress the 3-band or 6-band images coming out of PCA. The performance of different algorithms was assessed using four well-known performance metrics. Extensive experiments using actual Mastcam images have been performed to demonstrate the proposed framework. We observed that perceptually lossless compression can be achieved at a 10:1 compression ratio. In particular, the performance gain of an approach using a combination of PCA and X265 is at least 5 dBs in terms peak signal-to-noise ratio (PSNR) at a 10:1 compression ratio over that of JPEG when using our proposed approach.