This paper presents a new approach to index color images using the features extracted from the error diffusion block truncation coding (EDBTC). The EDBTC produces two color quantizers and a bitmap image, which are further processed using vector quantization (VQ) to generate the image feature descriptor. Herein two features are introduced, namely, color histogram feature (CHF) and bit pattern histogram feature (BHF), to measure the similarity between a query image and the target image in database. The CHF and BHF are computed from the VQ-indexed color quantizer and VQ-indexed bitmap image, respectively. The distance computed from CHF and BHF can be utilized to measure the similarity between two images. As documented in the experimental result, the proposed indexing method outperforms the former block truncation coding based image indexing and the other existing image retrieval schemes with natural and textural data sets. Thus, the proposed EDBTC is not only examined with good capability for image compression but also offers an effective way to index images for the content-based image retrieval system.

A prior work proposed by Chung-Wu considered an edge-based lookup table to obtain good inversed image quality, yet it suffers from some drawbacks in terms of image quality, memory consumption, and complexity. In this correspondence, an improved scheme is proposed to deal with these issues.

Inverse halftoning is a key technology to yield a continuous tone image from a halftone image. The main application is to make some image enhancement or further compression of halftones more feasible. Many former approaches have been proposed in the literature. Among these, a recent method proposed by Chung and Wu using edge-based lookup table achieves good image quality, where the edge feature is adopted to refine the trained look-up table (LUT). However, it has three deficiencies, including 1) the edge features are limited in some predefined cases, which cannot full represent every potential possibility, 2) the lookup table grows exponentially when extreme grayscales are attempted to be recorded, and 3) the trained lookup table cannot fully include all the cases, which leaves some halftone patterns in practice have no associated output grayscale. Chang et al.'s method employed one trained filter to compensate the halftone patterns that are not recorded in LUT. However, one filter cannot fully characterize the full textures in an image. In this study, the halftone patterns are classified according to its variance and then used to train the corresponding filter sets, which are then employed to provide higher prediction accuracy by inner product with the corresponding halftone patterns. As documented in the experimental results, the proposed inverse halftoning provides excellent performance in image quality and memory consumption than former approaches.

A halftone watermarking method of high quality, robustness, and capacity flexibility is presented in this paper. An objective halftone image quality evaluation method based on the human visual system obtained by least-mean-square is also introduced. In the encoder, the kernels-alternated error diffusion (KAEDF) is applied. This scheme is able to maintain the computational complexity at the same level as an ordinary error diffusion. Compared with Hel-Or using ordered dithering, the proposed KAEDF yields a better image quality through using error diffusion. Moreover, the Haar wavelet transform (HWT) decoding is employed instead of lookup table (LUT), so as to reduce the computational complexity. As documented in the experimental results, this technique is able to guard against degradation due to tampering, cropping, rotation, as well as print-and-scan processes in error-diffused halftone images.

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.

A high efficiency and good quality error-diffused halftoning is proposed in this paper. An objective halftone image quality evaluation method based on human visual system obtained by least-mean-square is also introduced. The error diffusion algorithm, first introduced by Floyd and Steinberg in 1975, is currently the most popular method of digital halftoning. However, some annoying shortcomings, such as patches of regular textures, worm effect, and computational complexity still need to be improved. Ostromoukhov proposed a three-element error diffusion solving the problems described above, and achieved excellent performance. In this paper, we further reduced the complexity with the proposed two-element error diffusion by cooperating with the proposed LMS-trained quality evaluation. As demonstrated in experiments, the proposed technique further reduced the complexity by 33% compared to Ostromoukhov's method, and it is still comparable in image quality.