Original Image Block Research Articles

Image Authentication and Restoration Using Block-Wise Variational Automatic Encoding and Generative Adversarial Networks

The Internet is a conduit for vast quantities of digital data, with the transmission of images being especially prevalent due to the widespread use of social media. However, this popularity has led to an increase in security concerns such as image tampering and forgery. As a result, image authentication has become a critical technology that cannot be overlooked. Recently, numerous researchers have focused on developing image authentication techniques using deep learning to combat various image tampering attacks. Nevertheless, image authentication techniques based on deep learning typically classify only specific types of tampering attacks and are unable to accurately detect tampered images or indicate the precise location of tampered areas. The paper introduces a novel image authentication framework that utilizes block-wise encoding through Variational Autoencoder and Generative Adversarial Network models. Additionally, the framework includes a classification mechanism to develop separate authentication models for different images. In the training phase, the image is first divided into blocks of the same size as training data. The goal is to enable the model to judge the authenticity of the image by blocks and to generate blocks similar to the original image blocks. In the verification phase, the input image can detect the authenticity of the image through the trained model, locate the exact position of the image tampering, and reconstruct the image to ensure the ownership.

ECFRNet: Effective corner feature representations network for image corner detection

Interest points (corners and blobs) play an important role in computer vision tasks such as image matching, image retrieval, and 3D reconstruction. Existing deep learning based interest point detection methods mainly focus on the interest point detection with high repeatability under image affine transformations while neglecting the importance of the characteristics of interest points. This will affect the detection and localization accuracy of interest points. In this paper, we design an effective corner feature representations network based on the characteristics of corners. The designed network has the ability to effectively learn corner feature information from images. A novel loss function is proposed to minimize the localization error between the corner positions of the original image block and the transformed image blocks. Furthermore, a novel corner detection architecture is proposed. The criteria on detection accuracy, localization accuracy, average repeatability, region repeatability, and image matching score are used to evaluate the proposed method against fourteen state-of-the-art methods. The experimental results show that the proposed performs significantly better than the state-of-the-arts.

Hierarchical volumetric transformer with comprehensive attention for medical image segmentation.

Transformer is widely used in medical image segmentation tasks due to its powerful ability to model global dependencies. However, most of the existing transformer-based methods are two-dimensional networks, which are only suitable for processing two-dimensional slices and ignore the linguistic association between different slices of the original volume image blocks. To solve this problem, we propose a novel segmentation framework by deeply exploring the respective characteristic of convolution, comprehensive attention mechanism, and transformer, and assembling them hierarchically to fully exploit their complementary advantages. Specifically, we first propose a novel volumetric transformer block to help extract features serially in the encoder and restore the feature map resolution to the original level in parallel in the decoder. It can not only obtain the information of the plane, but also make full use of the correlation information between different slices. Then the local multi-channel attention block is proposed to adaptively enhance the effective features of the encoder branch at the channel level, while suppressing the invalid features. Finally, the global multi-scale attention block with deep supervision is introduced to adaptively extract valid information at different scale levels while filtering out useless information. Extensive experiments demonstrate that our proposed method achieves promising performance on multi-organ CT and cardiac MR image segmentation.

A Novel Image Tamper Detection and Self-Recovery Algorithm Based on Watermarking and Chaotic System

With the development of image editing software techniques, the content integrity and authenticity of original digital images become more and more important in digital content security. A novel image tampering detection and recovery algorithm based on digital watermarking technology and a chaotic system is proposed, and it can effectively locate the tampering region and achieve the approximate recovery of the original image by using the hidden information. The pseudo-random cyclic chain is realized by the chaotic system to construct the mapping relationship between the image subblocks. It can effectively guarantee the randomness of the positional relationship between the hidden information and the original image block for the better ergodicity of the pseudo-random chain. The recovery value optimization algorithm can represent image information better. In addition to the traditional Level-1 recovery, a weight adaptive algorithm is designed to distinguish the original block from the primary recovery block, allowing 3 × 3 neighbor block recovery to achieve better results. The experimental results show that the hierarchical tamper detection algorithm makes tamper detection have higher precision. When facing collage attacks and large general tampering, it will have higher recovery image quality and better resistance performance.

An image encryption algorithm based on ZigZag transform and LL compound chaotic system

This paper proposes a new image encryption algorithm based on ZigZag transform and LL compound chaotic system. The improved ZigZag transform method and the Lü system are combined to scramble the original image block sub-channel, and complement it by a sorting scrambling algorithm with identification values. LL compound chaotic system is combined with Lü system and logistic chaotic map. It provides a secure and efficient key stream. The new chaotic encryption system destroys the pixel values and finally uses the adjacent-side XOR method to spread. The experimental results and security analysis show that the new algorithm has good encryption effect and can resist common attacks.

Separable reversible data hiding in encrypted images via adaptive embedding strategy with block selection

Abstract In this paper, an adaptive reversible data hiding scheme for encrypted images is proposed. Content owner uses an analogues stream-cipher and block permutation to encrypt non-overlapping blocks of original image through encryption key. Then, data hider classifies encrypted blocks into two sets corresponding to smooth and complex regions in original image. With data-hiding key, spare space is vacated to accommodate additional bits by compressing LSBs of the block set corresponding to smooth region. Separable operations of data extraction, direct decryption and image recovery are conducted by receiver according to the availability of encryption key and data-hiding key. Through an accurate prediction strategy, perfect image recovery is achieved. Since only a portion of blocks are modified during embedding, the directly-decrypted image quality is satisfactory. Also, more bits can be embedded into the blocks belonging to smooth set, hence, embedding rate is acceptable. Experimental results demonstrate the effectiveness of our scheme.

Reference Sharing Mechanism-Based Self-Embedding Watermarking Scheme with Deterministic Content Reconstruction

This paper presents a reference sharing mechanism-based self-embedding watermarking scheme. The host image is embedded with watermark bits including the reference data for content recovery and the authentication data for tampering location. The special encoding matrix derived from the generator matrix of selected systematic Maximum Distance Separable (MDS) code is adopted. The reference data is generated by encoding all the representative data of the original image blocks. On the receiver side, the tampered image blocks can be located by the authentication data. The reference data embedded in one image block can be shared by all the image blocks to restore the tampered content. The tampering coincidence problem can be avoided at the extreme. The maximal tampering rate is deduced theoretically. Experimental results show that, as long as the tampering rate is less than the maximal tampering rate, the content recovery is deterministic. The quality of recovered content does not decrease with the maximal tampering rate.

METHOD FOR IDENTIFYING THE RESULTS OF MULTI– AND POLYCLONING IN THE DIGITAL IMAGES

The modern level of development of information technology and computer science makes it easy to create, modify and manipulate of the digital images, which makes the issue of organization of expertise of their integrity is extremely urgent. One of the most common and frequently used software tools for unauthorized image changes is cloning, which in practice uses a post-processing image to hide it, making it difficult to detect clones and their pre-images. The efficiency of proposed method exceeds the efficiency of modern analogues. The aim of the research is development of a method for identifying the results of cloning in the digital images that is effective under multi– and polycloning conditions with additional significant perturbations. The main analyzed object during in the examination of a digital image, the formal representation of which is nxm-matrix with elements, is (n–q+1) (m–q+1)-matrix of minimal block differences that is matched to the image after a preliminary choice of qxq-block size, the plurality of which determines the overlapping. The element of matrix determines the magnitude Bij of the smallest difference of qxq-block, which corresponded to element , from any other qxq-block of the matrix. It is established that in the case of multicloning in the vicinity of local minima which responsible to the corresponding blocks of clones and the pre-image, the elements identical in values will be present, unlike most original blocks of the digital image. It is established that the histograms of the values of the matrix elements for the corresponding pairs of blocks from the clone and pre-image regions in the case of multicloning have characteristic features compared to histograms for pairs of blocks of original digital image’s regions: the maximum per-pixel difference in the first case is smaller than in the second; for the original digital image’s blocks the histogram mode is usually different from the "conditional zero" (the corresponding histogram column does not include zero elements R).The allowance for the revealed features of the neighborhoods of the local (global) minima of the matrix G and the histograms of the values R, it is possible to determine the corresponding blocks of clones and pre-images. The solution of this problem is proposed to be carried out by means of an analysis of the graph formed as follows. The blocks Bij, that belong to the domains of clones and pre-images, are associated with an unoriented graph E(V, X) with a set of vertices V and a set of edges X according to the following rule: each block Bij has a vertex with a label (i, j); the vertices (i, j) and (k, l) of the graph are adjacent, i.e. they form an edge if and only if the neighborhoods of elements gij and gkl of the same radius have the same value in the relevant elements in the matrix G. The number of connected components of the graph E(V, X) determines the number of different pre-images used in the polycloning process, and the blocks, for which the corresponding vertices fall into one connected component of the graph E(V, X), form the group “pre-image - its clones”.

General Principles of Integrity Checking of Digital Images and Application for Steganalysis

Abstract The new common approach for integrity checking of digital images is developed. The new features of formal parameters defining image are revealed, theoretically grounded and practically tested. The characteristics of the mutual arrangement of left and right singular vectors corresponding to the largest singular value of the image’s matrix (block of matrix) and the vector composed of singular numbers is obtained. Formal parameters are obtained using normal singular decomposition of matrix (block of matrix) which is uniquely determined. It is shown that for most blocks of original image (no matter lossy or lossless) the angle between the left (right) mentioned singular vector and vector composed of singular numbers is defined by the angle between the n-optimal vector and the vector of standard basis of the range corresponding dimension. It is shown that the determined feature brakes for the mentioned formal parameters in a non-original image. This shows the integrity violation of the image, i.e. the existence of the additional information embedded using steganography algorithms. So this can be used as a basis for development of new universal steganography methods and algorithms, and one example of the realization is proposed. The efficiency of the proposed algorithm won’t depend on the details of steganography method used for embedding. All the obtained results can be easily adapted for the digital video and audio analysis.

Compressed sensing image reconstruction using intra prediction

Compressed sensing (CS) provides a general signal acquisition framework that enables the reconstruction of sparse signals from a small number of linear measurements. In this article we present a CS image reconstruction algorithm using intra prediction method based on block-based CS image framework. The current reconstruction block is firstly predicted by its surrounding reconstructed pixels, and then its prediction residual will be reconstructed. Because the sparsity level of prediction residual is higher than its original image block, the performance of our proposed CS image reconstruction algorithm is significantly superior to the traditional CS reconstruction algorithm. Furthermore, total variation model is also used to suppress the blocking artifacts caused by intra prediction and measurement noise. Experimental results also show the competitive performance with respect to peak signal-to-noise ratio and subjective visual quality.

New Stereo Video Quality Assessment Metric for Three Dimensional Video Systems

Since traditional two dimensional video quality metrics are not suitable for evaluating stereo video, a new stereo video quality metric based on support vector regression (SVR) for three dimensional video systems is proposed in this paper. Firstly, three factors affecting the quality of stereo video are analyzed, namely left-view video quality, right-view video quality and difference between two views. Then, each of these factors is calculated respectively with measuring the singular vectors’ similarity between original image blocks and distorted image blocks and with temporal weighting using fluctuations of video frames’ spatial quality. Then, SVR is used to learn the relationships between the factors and the overall perceived quality of stereo video. Finally, the relationship is applied to predict the objective quality of stereo video. By applying the proposed metric to stereo video database, Person’s linear correlation coefficient is higher than 0.82 for all types of distortions and 0.81 for individual distortion, which outperforms the other existing metrics. Experimental results also show that, the proposed metric can achieve stable performance for all kinds of distortions and predict human perception well.

A New Fragile Watermarking Based on Chaos

For existing airspace fragile authentication watermarking algorithm positioning accuracy and security issues, this paper presents a fully-fragile watermarking based on chaos for the integrity of the image content authentication and tamper localization. The algorithm uses the original image block, the calculation of each pixel in the image block high-bit gray value as the image feature watermark information. The chaotic sequence is encrypted and determines the position of the watermark bit is embedded watermark information, tampering with the positioning accuracy of an image block of 2 × 2 pixels. Experimental results show that the algorithm is simple, safe, with good practice.

SBHCS: Spike based Histogram Comparison Steganalysis Technique

is the art of secretly transferring of data and steganalysis is the art of detecting that hidden data embedded in cover media. In the past years many powerful and robust methods of steganography and steganalysis have been reported in the literature. In this present work, a Steganalysis technique for Histogram-Shifting Based Data Hiding is designed to detect hidden data by using spike generation and template matching. The proposed work analyzes the characteristics of histogram changes during data hiding procedure, and then uses these features to distinguish between stego and original image.The presented work perform the steganalysis in four steps: First, an input image is filtered by using perwitt operator for edge detection. Second, the spike image is divided into 8x8 blocks and then histogram is generated for each block. Third, histogram of each block of stego-image and original image is compared by using 5 similarity measures (norm distance, cosine distance, Euclidean distance, Chi-squared distance, Entropy distance). Fourth, Neural Network (NN) is trained as a classifier to discriminate stego image from original image. Experimental results indicate that the proposed steganalysis method is better than the method proposed by Der-Chyuan Lou et. al.(1) and can effectively detect stego image at low bit rates.

A Blind Image Watermarking Scheme Utilizing BTC Bitplanes

This paper presents a novel image watermarking scheme utilizing Block Truncation Coding (BTC). This scheme uses BTC to guide the watermark embedding and extraction processes. During the embedding process, the original cover image is first partitioned into non-overlapping 4×4 blocks. Then, BTC is performed on each block to obtain its BTC bitplane, and the number of ‘1’s in the bitplane is counted. If the watermark bit to be embedded is ‘1’ and the number of ‘1’s is odd, or the watermark bit to be embedded is ‘0’ and the number of ‘1’s is even, then no change is made. Otherwise, by changing at most three pixels in the original image block, the number of ‘1’s (or ‘0’s) in the renewed bitplane are forced to be odd for the watermark bit ‘1’ or to be even for the watermark bit ‘0’. During the extraction process, BTC is first performed on each block to obtain its bitplane. If the number of ‘1’s in the bitplane is odd, then the embedded watermark bit is ‘1’. Otherwise, the embedded watermark bit is ‘0’. The experimental results show that the proposed watermarking method is semi-fragile except for the changes in brightness and contrast; therefore, the proposed method can be used for image authentication.

A Novel Digital Image Covert Communication Scheme Based on Generalized FCM in DCT Domain

A novel covert communication method of digital image is presented, based on generalized fuzzy c-means clustering (GFCM), human visual system (HVS) and discrete cosine transform (DCT). Therefore, the original image blocks are classified into two classes according to specified characteristic parameters. So one block is suited for embedding security information, but the other block is not. Hence the appropriate blocks can be selected in an image to embed the security information by selectively modifying the middle-frequency part of the original image in conjunction with HVS and DCT. Furthermore the maximal information strength is fixed based to the frequency masking. Also to improve performances of the proposed algorithm, the security information is modulated into the chaotic modulation array. The simulation results show that we can remarkably extract the hiding security information and can achieve good robustness with common signal distortion or geometric distortion and the quality of the embedded image is guaranteed.

A Novel Algorithm for Block Encryption of Digital Image Based on Chaos

This paper proposes a novel image block encryption algorithm based on three-dimensional Chen chaotic dynamical system. The algorithm works on 32-bit image blocks with a 192-bit secret key. The idea is that the key is employed to drive the Chen’s system to generate a chaotic sequence that is inputted to a specially designed function G, in which we use new 8x8 S-boxes generated by chaotic maps (Tang, 2005). In order to improve the robustness against differental cryptanalysis and produce desirable avalanche effect, the function G is iteratively performed several times and its last outputs serve as the keystreams to encrypt the original image block. The design of the encryption algorithm is described along with security analyses. The results from key space analysis, differential attack analysis, and information entropy analysis, correlation analysis of two adjacent pixels prove that the proposed algorithm can resist cryptanalytic, statistical and brute force attacks, and achieve a higher level of security. The algorithm can be employed to realize the security cryptosystems over the Internet.

Hiding Secret Data in an Image Using Codeword Imitation

This paper proposes a novel reversible data hiding scheme based on a Vector Quantization (VQ) codebook. The proposed scheme uses the principle component analysis (PCA) algorithm to sort the codebook and to find two similar codewords of an image block. According to the secret to be embedded and the difference between those two similar codewords, the original image block is transformed into a difference number table. Finally, this table is compressed by entropy coding and sent to the receiver. The experimental results demonstrate that the proposed scheme can achieve greater hiding capacity, about five bits per index, with an acceptable bit rate. At the receiver end, after the compressed code has been decoded, the image can be recovered to a VQ compressed image.

Efficient Image Deblocking Based on Postfiltering in Shifted Windows

We propose a simple yet effective deblocking method for JPEG compressed image through postfiltering in shifted windows (PSW) of image blocks. The MSE is compared between the original image block and the image blocks in shifted windows, so as to decide whether these altered blocks are used in the smoothing procedure. Our research indicates that there exists strong correlation between the optimal mean squared error threshold and the image quality factor Q, which is selected in the encoding end and can be computed from the quantization table embedded in the JPEG file. Also we use the standard deviation of each original block to adjust the threshold locally so as to avoid the over-smoothing of image details. With various image and bit-rate conditions, the processed image exhibits both great visual effect improvement and significant peak signal-to-noise ratio gain with fairly low computational complexity. Extensive experiments and comparison with other deblocking methods are conducted to justify the effectiveness of the proposed PSW method in both objective and subjective measures.

PHLST5: A Practical and Improved Version of Polyharmonic Local Sine Transform

We introduce a practical and improved version of the Polyharmonic Local Sine Transform (PHLST) called PHLST5. After partitioning an input image into a set of rectangular blocks, the original PHLST decomposes each block into a polyharmonic component and a residual. Each polyharmonic component solves a polyharmonic equation with the boundary conditions that match the values and normal derivatives of even orders along the boundary of the corresponding block with those of the original image block. Thanks to these boundary conditions, the residual component can be expanded into a Fourier sine series without facing the Gibbs phenomenon, and its Fourier sine coefficients decay faster than those of the original block. Due to the difficulty of estimating normal derivatives of higher orders, however, only the harmonic case (i.e., Laplace’s equation) has been implemented to date, which was called Local Laplace Sine Transform (LLST). In that case, the Fourier sine coefficients of the residual decay in the order O(‖k‖−3), where k is the frequency index vector. Unlike the original PHLST, PHLST5 only imposes the boundary values and the first order normal derivatives as the boundary conditions, which can be estimated using the information of neighbouring image blocks. In this paper, we derive a fast algorithm to compute a 5th degree polyharmonic function that satisfies such boundary conditions. Although the Fourier sine coefficients of the residual of PHLST5 possess the same decaying rate as in LLST, by using additional information of first order normal derivative from the boundary, the blocking artifacts are largely suppressed in PHLST5 and the residual component becomes much smaller than that of LLST. Therefore PHLST5 provides a better approximation result. We shall also show numerical experiments that demonstrate the superiority of PHLST5 over the original LLST in terms of the efficiency of approximation.

ADAPTIVE WATERMARKING AND PERFORMANCE ANALYSIS BASED ON IMAGE CONTENT

This paper presents a novel adaptive watermarking based on iteration mapping and image content. An original image is divided into non-overlapped blocks, which are analyzed by means of fractal dimension, and the feature blocks which contain edges and textures are further classified by variance characteristics into three different parts: edges, weak textures, and strong textures. The original watermark is a distinguishable gray image, which is scrambled and amended to form a watermark signal to be embedded. DCT is applied to all the original image blocks and the formed watermark is embedded into their middle-frequency coefficients with different strength. Performance analysis of adaptive watermark extraction is presented in details. Experimental results show that this algorithm is able to achieve a watermarked image with good perceptual invisibility, high security and strong robustness.