Compression of encrypted images with multi-layer decomposition

Abstract

This work proposes a novel scheme of lossy compression for encrypted gray images. In the encryption phase, the original image is decomposed into a sub-image and several layers of prediction errors, and the sub-image and prediction errors are encrypted using an exclusive-or operation and a pseudo-random permutation, respectively. Although a channel provider does not know the cryptographic key and the original content, he can still effectively reduce the amount of encrypted data by quantizing the permuted prediction errors on various layers, and an optimization method with rate-distortion criteria can be employed to select the values of quantization steps. At receiver side with the knowledge of cryptographic key, a decoder integrating dequantization, decryption and image reconstruction functions is used to retrieve the principal content of original image from the compressed data. Experimental result shows the rate-distortion performance of the proposed scheme is significantly better than that of previous technique.