Robust RDH Technique using Sorting and IPVO-based Pairwise PEE for Secure Communication

Nowadays, Reversible Data Hiding (RDH) is used extensively in information sensitive communication domains to protect the integrity of hidden data and the cover medium. However, most of the recently proposed RDH methods lack robustness. Robust RDH methods are required to protect the hidden data from security attacks at the time of communication between the sender and receiver. In this paper, we propose a Robust RDH scheme using IPVO based pairwise embedding. The proposed scheme is designed to prevent unintentional modifications caused to the secret data by JPEG compression. The cover image is decomposed into two planes namely HSB plane and LSB plane. As JPEG compression most likely modifies the LSBs of the cover image during compression, it is best not to hide the secret data into LSB planes. So, the proposed method utilizes a pairwise embedding to embed secret data into HSB plane of the cover image. High fidelity improved pixel value ordering (IPVO) based pairwise embedding ensures that the embedding performance of the proposed method is improved.

Neural evidence for image quality perception based on algebraic topology

In this paper, the algebraic topological characteristics of brain networks composed of electroencephalogram(EEG) signals induced by different quality images were studied, and on that basis, a neurophysiological image quality assessment approach was proposed. Our approach acquired quality perception-related neural information via integrating the EEG collection with conventional image assessment procedures, and the physiologically meaningful brain responses to different distortion-level images were obtained by topological data analysis. According to the validation experiment results, statistically significant discrepancies of the algebraic topological characteristics of EEG data evoked by a clear image compared to that of an unclear image are observed in several frequency bands, especially in the beta band. Furthermore, the phase transition difference of brain network caused by JPEG compression is more significant, indicating that humans are more sensitive to JPEG compression other than Gaussian blur. In general, the algebraic topological characteristics of EEG signals evoked by distorted images were investigated in this paper, which contributes to the study of neurophysiological assessment of image quality.

GENERAL TECHNOLOGY OF ENCRYPTION AND INTEGRATION OF DATA IN A PATTERN OF A PICTURE OF IMAGES THAT IS RESISTANT TO JPEG COMPRESSION

The object of the thesis is the use of steganographic methods for organizing a covert communication channel in a public channel, providing resistance to lossy compression. The aim of the thesis is to develop an algorithm for embedding data into bitmap images that is resistant to JPEG compression and attacks on the container. In this thesis, the features of the JPEG algorithm are investigated, steganographic methods of information protection are analyzed, and a steganographic algorithm is designed that is resistant to JPEG compression and attacks on the container. Additional security is provided by the polyalphabetic substitution cipher and user secret key used to encrypt the original message. The algorithm was developed using the Python 3 programming language, the NumPy, SciPy, MatPlotLib libraries and the Jupyter Lab package. The task was completed using standard mathematical and statistical methods and tools of the high-level programming language Python 3.

Analyzing Benford’s Law’s Powerful Applications in Image Forensics

The Newcomb–Benford law states that in a set of natural numbers, the leading digit has a probability distribution that decays logarithmically. One of its major applications is the JPEG compression of images, a field of great interest for domains such as image forensics. In this article, we study JPEG compression from the point of view of Benford’s law. The article focuses on ways to detect fraudulent images and JPEG quality factors. Moreover, using the image’s luminance channel and JPEG coefficients, we describe a technique for determining the quality factor with which a JPEG image is compressed. The algorithm’s results are described in considerably more depth in the article’s final sections. Furthermore, the proposed idea is applicable to any procedure that involves the analysis of digital images and in which it is strongly suggested that the image authenticity be verified prior to beginning the analyzing process.

Usage analysis of SVD, DWT and JPEG compression methods for image compression

Through image compression, can save bandwidth usage on telecommunication networks, accelerate image file sending time and can save memory in image file storage. Technique to reduce image size through compression techniques is needed. Image compression is one of the image processing techniques performed on digital images with the aim of reducing the redundancy of the data contained in the image so that it can be stored or transmitted efficiently. This research analyzed the results of image compression and measure the error level of the image compression results. The analysis to be carried out is in the form of an analysis of JPEG compression techniques with various types of images. The method of measuring the compression results uses the MSE and PSNR methods. Meanwhile, to determine the percentage level of compression using the compression ratio calculation. The average ratio for JPEG compression was 0.08605, the compression rate was 91.39%. The average compression ratio for the DWT method was 0.133090833, the compression rate was 86.69%. The average compression ratio of the SVD method was 0.101938833 and the compression rate was 89.80%.