Joint JPEG compression and detection resistant performance enhancement for adaptive steganography using feature regions selection

Since it is difficult to acquire a strong JPEG compression resistant ability while achieving a good detection resistant performance for current information hiding algorithms, a JPEG compression and detection resistant adaptive steganography algorithm using feature regions is proposed. Based on the proposed feature region extraction and selection algorithms, the embedding domain robust to JPEG compression and containing less embedding distortion can be obtained. Utilizing the current distortion functions, the distortion value of DCT coefficients in the embedding domain can be calculated. Combined with error correct coding and STCs, the messages are embedded into the cover images with minimum embedding distortion, and can be extracted with high accuracy after JPEG compression, hence, the JPEG compression and detection resistant performance are enhanced at the same time. The experimental results demonstrate that comparing with current J-UNIWARD steganography under quality factor 85 of JPEG compression, the extraction error rates decrease from above 20 % to nearly 0, while the stego images remain a better detection resistant performance comparing with the current JPEG compression and detection resistant adaptive steganography algorithm.