Improvement of JPEG compression efficiency using information hiding and image restoration

The application of information hiding to image compression is investigated to improve compression efficiency for JPEG color images. In the proposed method, entropy-coded DCT coefficients of chrominance components are embedded into DCT coefficients of the luminance component. To recover an image in the face of the degradation caused by compression and embedding, an image restoration method is also applied. Experiments show that the use of both information hiding and image restoration is most effective to improve compression efficiency

Invertible Rescaling Network and Its Extensions

Image rescaling is a commonly used bidirectional operation, which first downscales high-resolution images to fit various display screens or to be storage- and bandwidth-friendly, and afterward upscales the corresponding low-resolution images to recover the original resolution or the details in the zoom-in images. However, the non-injective downscaling mapping discards high-frequency contents, leading to the ill-posed problem for the inverse restoration task. This can be abstracted as a general image degradation-restoration problem with information loss. In this work, we propose a novel invertible framework to handle this general problem, which models the bidirectional degradation and restoration from a new perspective, i.e. invertible bijective transformation. The invertibility enables the framework to model the information loss of pre-degradation in the form of distribution, which could mitigate the ill-posed problem during post-restoration. To be specific, we develop invertible models to generate valid degraded images and meanwhile transform the distribution of lost contents to the fixed distribution of a latent variable during the forward degradation. Then restoration is made tractable by applying the inverse transformation on the generated degraded image together with a randomly-drawn latent variable. We start from image rescaling and instantiate the model as Invertible Rescaling Network (IRN), which can be easily extended to the similar decolorization-colorization task. We further propose to combine the invertible framework with existing degradation methods such as image compression for wider applications. Experimental results demonstrate the significant improvement of our model over existing methods in terms of both quantitative and qualitative evaluations of upscaling and colorizing reconstruction from downscaled and decolorized images, and rate-distortion of image compression.Comment: Accepted by IJC

Framework for reversible data hiding using cost-effective encoding system for video steganography

Importances of reversible data hiding practices are always higher in contrast to any conventional data hiding schemes owing to its capability to generate distortion free cover media. Review of existing approaches on reversible data hiding approaches shows variable scheme mainly focussing on the embedding mechanism; however, such schemes could be furthermore improved using encoding scheme for optimal embedding performance. Therefore, the proposed manuscript discusses about a cost-effective scheme where a novel encoding scheme has been used with larger block sizes which reduces the dependencies over larger number of blocks. Further a gradient-based image registration technique is applied to ensure higher quality of the reconstructed signal over the decoding end. The study outcome shows that proposed data hiding technique is proven better than existing data hiding scheme with good balance between security and restored signal quality upon extraction of data

A NOVEL JOINT PERCEPTUAL ENCRYPTION AND WATERMARKING SCHEME (JPEW) WITHIN JPEG FRAMEWORK

Due to the rapid growth in internet and multimedia technologies, many new commercial applications like video on demand (VOD), pay-per-view and real-time multimedia broadcast etc, have emerged. To ensure the integrity and confidentiality of the multimedia content, the content is usually watermarked and then encrypted or vice versa. If the multimedia content needs to be watermarked and encrypted at the same time, the watermarking function needs to be performed first followed by encryption function. Hence, if the watermark needs to be extracted then the multimedia data needs to be decrypted first followed by extraction of the watermark. This results in large computational overhead. The solution provided in the literature for this problem is by using what is called partial encryption, in which media data are partitioned into two parts - one to be watermarked and the other is encrypted. In addition, some multimedia applications i.e. video on demand (VOD), Pay-TV, pay-per-view etc, allow multimedia content preview which involves „perceptual‟ encryption wherein all or some selected part of the content is, perceptually speaking, distorted with an encryption key. Up till now no joint perceptual encryption and watermarking scheme has been proposed in the literature. In this thesis, a novel Joint Perceptual Encryption and Watermarking (JPEW) scheme is proposed that is integrated within JPEG standard. The design of JPEW involves the design and development of both perceptual encryption and watermarking schemes that are integrated in JPEG and feasible within the „partial‟ encryption framework. The perceptual encryption scheme exploits the energy distribution of AC components and DC components bitplanes of continuous-tone images and is carried out by selectively encrypting these AC coefficients and DC components bitplanes. The encryption itself is based on a chaos-based permutation reported in an earlier work. Similarly, in contrast to the traditional watermarking schemes, the proposed watermarking scheme makes use of DC component of the image and it is carried out by selectively substituting certain bitplanes of DC components with watermark bits. vi ii Apart from the aforesaid JPEW, additional perceptual encryption scheme, integrated in JPEG, has also been proposed. The scheme is outside of joint framework and implements perceptual encryption on region of interest (ROI) by scrambling the DCT blocks of the chosen ROI. The performances of both, perceptual encryption and watermarking schemes are evaluated and compared with Quantization Index modulation (QIM) based watermarking scheme and reversible Histogram Spreading (RHS) based perceptual encryption scheme. The results show that the proposed watermarking scheme is imperceptible and robust, and suitable for authentication. Similarly, the proposed perceptual encryption scheme outperforms the RHS based scheme in terms of number of operations required to achieve a given level of perceptual encryption and provides control over the amount of perceptual encryption. The overall security of the JPEW has also been evaluated. Additionally, the performance of proposed separate perceptual encryption scheme has been thoroughly evaluated in terms of security and compression efficiency. The scheme is found to be simpler in implementation, have insignificant effect on compression ratios and provide more options for the selection of control factor

Information similarity metrics in information security and forensics

We study two information similarity measures, relative entropy and the similarity metric, and methods for estimating them. Relative entropy can be readily estimated with existing algorithms based on compression. The similarity metric, based on algorithmic complexity, proves to be more difficult to estimate due to the fact that algorithmic complexity itself is not computable. We again turn to compression for estimating the similarity metric. Previous studies rely on the compression ratio as an indicator for choosing compressors to estimate the similarity metric. This assumption, however, is fundamentally flawed. We propose a new method to benchmark compressors for estimating the similarity metric. To demonstrate its use, we propose to quantify the security of a stegosystem using the similarity metric. Unlike other measures of steganographic security, the similarity metric is not only a true distance metric, but it is also universal in the sense that it is asymptotically minimal among all computable metrics between two objects. Therefore, it accounts for all similarities between two objects. In contrast, relative entropy, a widely accepted steganographic security definition, only takes into consideration the statistical similarity between two random variables. As an application, we present a general method for benchmarking stegosystems. The method is general in the sense that it is not restricted to any covertext medium and therefore, can be applied to a wide range of stegosystems. For demonstration, we analyze several image stegosystems using the newly proposed similarity metric as the security metric. The results show the true security limits of stegosystems regardless of the chosen security metric or the existence of steganalysis detectors. In other words, this makes it possible to show that a stegosystem with a large similarity metric is inherently insecure, even if it has not yet been broken

Recovering Sign Bits of DCT Coefficients in Digital Images as an Optimization Problem

Recovering unknown, missing, damaged, distorted or lost information in DCT coefficients is a common task in multiple applications of digital image processing, including image compression, selective image encryption, and image communications. This paper investigates recovery of a special type of information in DCT coefficients of digital images: sign bits. This problem can be modelled as a mixed integer linear programming (MILP) problem, which is NP-hard in general. To efficiently solve the problem, we propose two approximation methods: 1) a relaxation-based method that convert the MILP problem to a linear programming (LP) problem; 2) a divide-and-conquer method which splits the target image into sufficiently small regions, each of which can be more efficiently solved as an MILP problem, and then conducts a global optimization phase as a smaller MILP problem or an LP problem to maximize smoothness across different regions. To the best of our knowledge, we are the first who considered how to use global optimization to recover sign bits of DCT coefficients. We considered how the proposed methods can be applied to JPEG-encoded images and conducted extensive experiments to validate the performances of our proposed methods. The experimental results showed that the proposed methods worked well, especially when the number of unknown sign bits per DCT block is not too large. Compared with other existing methods, which are all based on simple error-concealment strategies, our proposed methods outperformed them with a substantial margin, both according to objective quality metrics (PSNR and SSIM) and also our subjective evaluation. Our work has a number of profound implications, e.g., more sign bits can be discarded to develop more efficient image compression methods, and image encryption methods based on sign bit encryption can be less secure than we previously understood.Comment: 13 pages, 8 figure