Adaptive Lossless Data Hiding Scheme for SMVQ-Compressed Images using SOC Coding

Abstract

Lossless data hiding recovers original images precisely after secret data are extracted. Therefore, it has received considerable attention among researchers. This paper offers an adaptive lossless data hiding scheme that is based on the search-order coding (SOC) algorithm for side match vector quantization (SMVQ) compressed images. By combining SOC coding with the SMVQ algorithm, compression performance is further improved while a large amount of free space is generated to hide secret data during the data embedding phase. In the extracting phase, simple steps are used to extract that embedded secret data. The same index table can be reconstructed on the receiver side, which ensures that this proposed scheme can restore the original cover image exactly. Experimental results have demonstrated that the proposed scheme yields a higher embedding rate and a lower compression rate than other related VQ and SMVQ based data hiding schemes.