Efficient Compression of Secured Images using Subservient Data and Huffman Coding

While transmitting redundant data through an insecure and bandwidth limited channel, it is mandatory to encrypt and compress it. Generally encryption is followed by compression as the statistical properties of encrypted images are not suitable for applying conventional compression schemes. The problem is that many situations demand the reverse procedure. This paper proposes a scheme of compressing encrypted data with the help of a subservient data and Huffman coding. For encrypting the original image, it is manipulated with a pseudorandom number sequence generated using a secret key. The subservient data is also created by the content owner. The encrypted data is then compressed using a quantization mechanism and Huffman coding. For quantizing the image the subservient data produced by the content owner is used. The quantized values are then coded using Huffman coding. At the reconstruction side the principal content of the data is reconstructed. Experimental results show that the compression ratio distortion performance of this method is superior to the existing Techniques. The compression ratio of encrypted image is improved to the range 10 to 20. (C) 2016 The Authors. Published by Elsevier Ltd.