Quality Compressed Steganography Using Hidden Referenced Halftoning

Abstract

Block truncation coding is an efficient compression technique while offering good image quality. Nonetheless, the blocking effect inherent in BTC causes severe perceptual artifact in high compression ratio applications. In this paper, an Error-Diffused Block Truncation Coding (EDBTC) is proposed to solve this problem. According to the EDBTC, the error caused by the difference between the original grayscale pixel value and the correspondingly high or low mean substitute is diffused to the predefined neighborhood, and hence the average grayscale will be maintained invariably. In addition, since the compressed data are widely distributed in the internet transmission, the extra message delivering in a secret way also highly raises attention recently. In this paper, we propose the Compressed Steganography using Hidden Referenced Halftoning (CSHRH), which cooperates with error diffusion and ordered dithering to achieve the objective of secret communication in BTC images. As documented in the experimental results, a low complexity with good image quality approach is obtained. Moreover, CSHRH is extended to Secret-Sharing Steganography (SSS) and Color Extension Steganography (CES). The SSS is able to distribute message into multiple host images and hence improves the security. The CES is able to deliver secure message via color embedded CSHRH image. Both extensions are also with an extra benefit of achieving high capacity message convection.Key words: block truncation coding, steganography, error diffusion, ordered dithering, secret sharing INTRODUCTIONBlock truncation coding (BTC) was first introduced by Delp and Mitchell in 1979 [1]. The basic concept is to divide the image into non-overlapped blocks, each pixel in a block is replaced by either high or low mean while preserving the first and second moments of the block. The main advantages of the method are the good image quality and the relatively lower complexity compared to the modern compression techniques, e.g. JPEG or JPEG2000. However, the image quality obtained by the traditional BTC degrades rapidly with the increase of the coding gain. Several investigations have addressed in the issue of further improving the image quality or coding gain of the BTC [2]-[6], Some of those include using vector quantization (VQ) to further compress the overhead information of the BTC outputs [2]; applying a hybrid coding model by using the LUT-based VQ to fast encode the bit-map, and the DCT to encode the high-mean and low-mean subimages [3]; adopting universal Hamming codes and a differential pulse code modulation (PCM) to the bit plane and the side information of BTC to reduce bit rate and preserving the low computational complexity [4]; using moment and visual information content to determine the regions for further BTC processing or neglecting in order to reduce the computation overhead, which preserves moderated quality while remaining the possibility of real time processing [5]; employing two-step criterion to determine if a block is encoded with neighboring coded blocks,...