Information preserving storage of remote sensing data: virtually lossless compression of optical and SAR images

We propose near-lossless compression, i.e., strictly bounded absolute reconstruction error, for remote sensing images. First, a classified DPCM scheme is presented for optical data. Then, an original approach to near-lossless compression of SAR images is presented, that is based on the Rational Laplacian Pyramid (RLP). The baseband icon of the RLP is DPCM encoded, the intermediate layers are uniformly quantized, and the bottom layer is is logarithmically quantized. As a consequence, the pixel ratio of original to decoded image can be strictly bounded by the quantization step size of the bottom layer of RLP. The steps on the other layers are arbitrary because of the quantization noise feedback loops at the encoder. If reconstruction errors fall within the boundaries of the noise distributions, either thermal noise, or speckle, the decoded images will be virtually lossless, even though their encoding was not strictly reversible.