SMOOTHING AND OPTIMAL COMPRESSION OF ENCRYPTED GRAY SCALE IMAGES

Compression efficiency of encrypted real-world sources such as images can be improved by exploiting source dependency. Lossless compression of encrypted images can be achieved through SlepianWolf coding. In this correspondence, we propose a resolution progressive compression scheme which compresses an encrypted image progressively in resolution, such that the decoder can observe a lowresolution version of the image, study local statistics based on it, and use the statistics to decode the next resolution level. Good performance is observed both theoretically and experimentally. We deploy smoothing for images at the receiver to mitigate noise.