Compression of Encrypted Images Using Set Partitioning In Hierarchical Trees Algorithm
G. Sarika, Harikuttan Unnithan, Smitha Peter, P. Predeep, Mrinal K. Thakur, M. K. Ravi Varma · AIP conference proceedings · 2011
When it is desired to transmit redundant data over an insecure channel, it is customary to encrypt the data. For encrypted real world sources such as images, the use of Markova properties in the slepian‐wolf decoder does not work well for gray scale images. Here in this paper we propose a method of compression of an encrypted image. In the encoder section, the image is first encrypted and then it undergoes compression in resolution. The cipher function scrambles only the pixel values, but does not shuffle the pixel locations. After down sampling, each sub‐image is encoded independently and the resulting syndrome bits are transmitted. The received image undergoes a joint decryption and decompression in the decoder section. By using the local statistics based on the image, it is recovered back. Here the decoder gets only lower resolution version of the image. In addition, this method provides only partial access to the current source at the decoder side, which improves the decoder’s learning of the source statistics. The source dependency is exploited to improve the compression efficiency. This scheme provides better coding efficiency and less computational complexity.