Enhanced imperialist competitive algorithm based efficient reversible data hiding technique

Abstract

This paper presents a novel reversible data hiding into a Vector Quantization (VQ) and Side Match Vector Quantization (SMVQ) based compression image to embed high capacity secret bits and recover cover image after data extraction. For optimal embedding capacity and to achieve exact recovery of cover image, this paper uses Enhanced Imperialist Competitive Algorithm (EICA). The threshold value is determined by the fitness function contrast sensitivity in EICA in order to signify embedding rate of each region in a cover image based on the size of the secret message. During data hiding, the output size of code stream is preserved in hiding two secret bits into a single index value. Discrete Cosine Transform (DCT) and Burrows Wheeler Transform (BWT) is applied before quantization for exact recovery of cover image and to achieve high compression ratio. Excellent energy compaction is provided by DCT and BWT reorders the symbols according to their context. Thus the proposed method provides a novel technique to embed secret bits into the cover image and compresses the embedded image. The output will be in the form of code streams with preserved size. The experimental results show that the proposed technique achieves high embedding capacity and compression rate.