Robust Image Compression Algorithm using Discrete Fractional Cosine Transform

The discrete fractional Fourier transform become paradigm in signal processing. This transform process the signal in joint time-frequency domain. The attractive and very important feature of DFrCT is an availability of extra degree of one free parameter that is provided by fractional orders and due to which optimization is possible. Less execution time and easy implementation are main advantages of proposed algorithm. The merit of effectiveness of proposed technique over existing technique is superior due to application of discrete fractional cosine transform by which higher compression ratio and PSNR are obtained without any artifacts in compressed images. The novelty of the proposed algorithm is no artifacts in compressed image along with good CR and PSNR. Compression ratio (CR) and peak signal to noise ratio (PSNR) are quality parameters for image compression with optimum fractional order.

Asymmetric Data Hiding for Compressed Images with High Payload and Reversibility

Hiding secret data in digital images is an attractive topic in the information security research area. Because the data-embedded stego image looks exactly the same as a regular image, transmitting secret data with stego images does not draw the attention of eavesdroppers, thus fulfilling the goal of information security. Many reversible data hiding (RDH) methods for absolute moment block truncation coding (AMBTC) compressed images have been proposed. These methods hide secret data in an AMBTC-compressed image to produce a stego image and transmit it to the recipient. Upon receiving the stego image, the recipient can extract the secret data and recover the AMBTC-compressed image. In this paper, we propose an RDH scheme for AMBTC-compressed images with an asymmetric embedding rule. Using the AMBTC-compressed version as the basis, the proposed embedding scheme always modifies a pixel value toward its original value with a step size (bitrate) proportional to the gap width. Therefore, the visual quality of the stego image is better than the referred AMBTC version. Additionally, as a result of the adaptive bitrate strategy, the data embedding capacity of the proposed scheme outperforms that of state-of-the-art methods. The security of the resulting stego images was also tested by RS-steganalysis. Experimental results show that the overall performance of the proposed scheme is satisfactory. We revised it, please confirm.

Detecting Non-Aligned Double JPEG Compression Based on Amplitude-Angle Feature

Due to the popularity of JPEG format images in recent years, JPEG images will inevitably involve image editing operation. Thus, some tramped images will leave tracks of Non-aligned double JPEG ( NA-DJPEG ) compression. By detecting the presence of NA-DJPEG compression, one can verify whether a given JPEG image has been tampered with. However, only few methods can identify NA-DJPEG compressed images in the case that the primary quality factor is greater than the secondary quality factor. To address this challenging task, this article proposes a novel feature extraction scheme based optimized pixel difference ( OPD ), which is a new measure for blocking artifacts. Firstly, three color channels (RGB) of a reconstructed image generated by decompressing a given JPEG color image are mapped into spherical coordinates to calculate amplitude and two angles (azimuth and zenith). Then, 16 histograms of OPD along the horizontal and vertical directions are calculated in the amplitude and two angles, respectively. Finally, a set of features formed by arranging the bin values of these histograms is used for binary classification. Experiments demonstrate the effectiveness of the proposed method, and the results show that it significantly outperforms the existing typical methods in the mentioned task.

Securing LSB embedding against structural steganalysis

This work explores the extent to which LSB embedding can be made secure against structural steganalysis through a modification of cover image statistics prior to message embedding. LSB embedding disturbs the statistics of consecutive k-tuples of pixels, and a kth-order structural attack detects hidden messages with lengths in proportion to the size of the imbalance amongst sets of k-tuples. To protect against kth-order structural attacks, cover modifications involve the redistribution of k-tuples among the different sets so that symmetries of the cover image are broken, then repaired through the act of LSB embedding so that the stego image bears the statistics of the original cover. We find this is only feasible for securing against up to 3rd-order attacks since higher-order protections result in virtually zero embedding capacities. To protect against 3rd-order attacks, we perform a redistribution of triplets that also preserves the statistics of pairs. This is done by embedding into only certain pixels of each sextuplet, constraining the maximum embedding rate to be ⩽ 2 / 3 bits per channel. Testing on a variety of image formats, we report best performance for JPEG-compressed images with a mean maximum embedding rate undetectable by 2nd- and 3rd-order attacks of 0.21 bpc.

A High Fidelity Authentication Scheme for AMBTC Compressed Image Using Reference Table Encoding

In this paper, we propose a high-quality image authentication method based on absolute moment block truncation coding (AMBTC) compressed images. The existing AMBTC authentication methods may not be able to detect certain malicious tampering due to the way that the authentication codes are generated. In addition, these methods also suffer from their embedding technique, which limits the improvement of marked image quality. In our method, each block is classified as either a smooth block or a complex one based on its smoothness. To enhance the image quality, we toggle bits in bitmap of smooth block to generate a set of authentication codes. The pixel pair matching (PPM) technique is used to embed the code that causes the least error into the quantization values. To reduce the computation cost, we only use the original and flipped bitmaps to generate authentication codes for complex blocks, and select the one that causes the least error for embedment. The experimental results show that the proposed method not only obtains higher marked image quality but also achieves better detection performance compared with prior works.

Dual-Domain Fusion Convolutional Neural Network for Contrast Enhancement Forensics

Contrast enhancement forensics techniques have always been of great interest for the image forensics community, as they can be an effective tool for recovering image history and identifying tampered images. Although several contrast enhancement forensic algorithms have been proposed, their accuracy and robustness against some kinds of processing are still unsatisfactory. In order to attenuate such deficiency, in this paper, we propose a new framework based on dual-domain fusion convolutional neural network to fuse the features of pixel and histogram domains for contrast enhancement forensics. Specifically, we first present a pixel-domain convolutional neural network to automatically capture the patterns of contrast-enhanced images in the pixel domain. Then, we present a histogram-domain convolutional neural network to extract the features in the histogram domain. The feature representations of pixel and histogram domains are fused and fed into two fully connected layers for the classification of contrast-enhanced images. Experimental results show that the proposed method achieves better performance and is robust against pre-JPEG compression and antiforensics attacks, obtaining over 99% detection accuracy for JPEG-compressed images with different QFs and antiforensics attack. In addition, a strategy for performance improvements of CNN-based forensics is explored, which could provide guidance for the design of CNN-based forensics tools.

Survey on Data Hiding Based on Block Truncation Coding

Data hiding technology has achieved many technological developments through continuous research over the past 20 years along with the development of Internet technology and is one of the research fields that are still receiving attention. In the beginning, there were an intensive amount of studies on digital copyright issues, and since then, interest in the field of secret communications has been increasing. In addition, research on various security issues using this technology is being actively conducted. Research on data hiding is mainly based on images and videos, and there are many studies using JPEG and BMP in particular. This may be due to the use of redundant bits that are characteristic of data hiding techniques. On the other hand, block truncation coding-based images are relatively lacking in redundant bits useful for data hiding. For this reason, researchers began to pay more attention to data hiding based on block-cutting coding. As a result, many related papers have been published in recent years. Therefore, in this paper, the existing research on data hiding technology of images compressed by block-cut coding among compressed images is summarized to introduce the contents of research so far in this field. We simulate a representative methodology among existing studies to find out which methods are effective through experiments and present opinions on future research directions. In the future, it is expected that various data hiding techniques and practical applications based on modified forms of absolute moment block truncation coding will continue to develop.

Two-Layer Reversible Data Hiding for VQ-Compressed Images Based on De-Clustering and Indicator-Free Search-Order Coding

During transmission of digital images, secret messages can be embedded using data hiding techniques. Such techniques can transfer private secrets without drawing the attention of eavesdroppers. To reduce the amount of transmitted data, image compression methods are widely applied. Hiding secret data in compressed images is a hot issue recently. In this paper, we apply the de-clustering concept and the indicator-free search-order coding (IFSOC) technique to hide information into vector quantization (VQ) compressed images. Experimental results show that the proposed two-layer reversible data hiding scheme for IFSOC-encoded VQ index table can hide a large amount of secret data among state-of-the-art methods with a relatively lower bit rate and high security.