Color Components Of Image Research Articles

VSDHS-CIEA: Color image encryption algorithm based on novel variable-structure discrete hyperchaotic system and cross-plane confusion strategy

Recently, the color image encryption algorithm based on chaos theory has become the focus of current research. When encrypting color images, the common practice is to treat color images as different gray components and process them severally, which results in more redundancy and low efficiency. The security of chaotic cryptosystems also depends on the performance of the chaotic systems adopted. The structures of many current chaotic systems are fixed, making their behaviors highly predictable. Additionally, the range of chaotic region parameters is limited and discontinuous. To solve the above-mentioned problems, a new color image encryption algorithm (CIEA) using fractal and chaos theory is presented, which fully considers the inherent connection among the RGB components of color images. First, we propose a variable-structure discrete hyperchaotic system (VSDHS) to solve the dilemma encountered by existing chaotic systems. The excellent dynamic properties of VSDHS are verified by rigorous mathematical proof and simulation performance analyses. Then, VSDHS-CIEA is designed using fractal theory and VSDHS. The algorithm makes full use of the inherent connection among the different components of color images and performs cross-plane confusion. Simulations and performance analyses prove that VSDHS-CIEA has higher security and better performance than some representative image encryption algorithms.

Мethod for determining the level of similarity of images by color component based on correlation analysis and color space quantization

The color component of an image is the basic information about the image. Color determines the mood of an image, its concept, and can also serve as a semantic accent. Obtaining information about the color component of an image is necessary when solving various kinds of tasks. For example, the task of finding similar images according to the content, as information about the color component can be combined with other metadata of the image and more fully describe its concept. In this paper authors describe the physical representation of color, the most popular digital representations of color, ways of extracting color components of an image, such as color histograms, quantization, coherent vectors and K -means, and ways of comparing color components of images, such as Euclidean distance, cosine distance, Manhattan distance, Chebyshev distance, Jaccard index, correlation analysis, Pearson's agreement test and Bhattacharya distance. It is suggested that the use of histogram comparison and vector comparison methods is acceptable for comparing the color components of images, since color histograms can be written in vector form. The authors conduct an experiment in which a human expert reviews combinations of color component acquisition and comparison methods and completes a test protocol based on the criteria highlighted by the authors. The criteria were based on the human interpretability of the results of the methods of determining and comparing the color component. On the basis of the experiment it has been determined that the best of the methods of comparison of color components of the definition images considered in the article is the correlation analysis of color histograms of images, which have been extracted in a quantized color space, because this approach meets all the criteria for testing and keeps the greatest amount of information about the color component.

A Hybrid Method for Enhancement of Both Contrast Distorted and Low-Light Images

Many different histogram equalization (HE)-based image enhancement methods have been developed to overcome the problems of low or high image brightness, contrast sensitivity, and difficulty in revealing details of dark areas under low-light environments. In this paper, a novel image enhancement method based on HE and adaptive gamma correction with weight distribution (AGCWD) is proposed for natural and effective image enhancement. In this method, histogram stretching is performed on Red–Green–Blue (RGB) color components of image, and then the color space of RGB image is converted to Hue–Saturation–Intensity (HSI) color space. The histograms of S and I components are divided into sub-histograms according to the exposure threshold. The underexposure regions are enhanced with a new AGCWD. Then, the color space of HSI image is converted to RGB color space. Finally, the HE is applied to the input image with the obtained image histogram map. Thus, the method has not only effectively prevented the over-enhancement of the contrast but also obtained the quality and natural enhanced image. The proposed method is compared with the most known contrast enhancement methods and low-light enhancement methods. Experimental results have supported that the proposed method outperforms other methods in terms of both visual perception and objective evaluation.

Color image encryption based on 2D enhanced hyperchaotic logistic-sine map and two-way Josephus traversing

To improve the chaotic behavior of the chaotic map, this paper proposes a new two-dimensional (2D) chaotic map, namely, 2D enhanced hyperchaotic Logistic-sine map (2D-EHLM), which is derived from the idea of the 2D Logistic map and the Sine map. The performance analyses demonstrate that the 2D-EHLM has significantly better hyperchaotic property, unpredictability characteristics in terms of their Lyapunov exponents, trajectories, and 0-1test in comparison to some existing 2D chaotic maps. Such as the 2D-EHLM performs chaotic behavior when their control parameter μ within (−3,4), which indicates a large chaotic range comparing with other 2D dynamical systems. To investigate its application, this paper proposes a new image confusion strategy based on the two-way Josephus traversing (TJT) to efficiently scramble the color image components and pixel positions. Combining 2D-EHLM and TJT operation, a new color image encryption scheme is proposed. The stimulation experiments and security analysis demonstrate that the proposed algorithm is able to protect the image information with a high security as well as to resist common types of attacks, which also verify the superior hyperchaotic behaviors of the 2D-EHLM from the aspect of encryption effect.

Dynamic Exploration of a Controllable Thermosensitive Neuron Model and Its Applications

A specific functional electric component is connected to any branch of the neural circuit, which can enhance the corresponding biological function as a smart sensor, whereas the temperature has a significant effect on the firing rhythm of neurons by regulating channel conductance and excitability. So for this paper, a controllable thermosensitive neuron model is established by paralleling two thermistors in the FitzHugh–Nagumo neural circuit. Especially, the thermistors are controlled by two switches, where three working modes can be selected, for which bifurcation diagrams, time response diagrams and spectral entropy (SE) complexity are used to analyze the dynamic behaviors in different operating modes. It is found that any modulation of thermistor can regulate the branch current and output voltage completely under the three working modes. More importantly, the neuronal activities show different mode transitions from periodic to bursts or chaos. The superior dynamic characteristics and rich firing behavior make the new model more suitable for images encryption. For this purpose, we consider switching the three thermosensitive neuron models continuously to obtain more complex chaotic sequences. Next, based on the feature of high pixel correlation among color image components, a 3D projection scrambling algorithm is designed, and then employed in combination with the universal gravitational diffusion method to propose a color image encryption scheme. In addition, the designed algorithm is executed by encrypting and decrypting some color images. The experimental results show that the algorithm cannot only encrypt the color image effectively, but also has no limitation on the size of the test image. It is worth mentioning that the designed encrypted algorithm has satisfactory security performance and considerable robustness against noise attacks and shearing attacks. The exploration of this paper about the thermosensitive neuron model and its application may provide some theoretical guidance and experimental basis in the field of secure communication.

A Lossless Compression and Encryption Method for Remote Sensing Image Using LWT, Rubik’s Cube and 2D-CCM

This paper proposes a lossless encryption–compression algorithm for large-scale remote sensing images. Firstly, the red, green and blue components of color image are compressed by a lossless predictive encoding. Then, the lifting wavelet transform (LWT) is used to decompose the encoding results. And a new Rubik’s cube transformation is introduced to scramble the decomposed coefficients, which uses the chaotic sequence generated by 2D Cubic–Chebyshev map (2D-CCM). The initial values of 2D-CCM are obtained from the chi-square test values of the three components, which leads to the algorithm related to the plaintext image. After that, the scrambling coefficients are thresholding, and the position sequences generated in the process are encrypted and compressed by the proposed encrypted run-length encoding (E-RLE). The processed coefficients are further compressed by Huffman encoding. At the end, the final results are obtained by a novel helix diffusion which is related to the chaotic sequence. Experimental results show that, this algorithm achieves higher lossless compression ratio with lower time complexity, and the encryption scheme has higher security.

Light-field image watermarking based on geranion polar harmonic Fourier moments

Light-field images provide a spatial and angular description of the light, and they can capture rich visual information in the natural world. In recent years, the research on light-field imaging has achieved many fruitful results. As more and more people are now focusing their attention to light-field imaging, the copyright protection of light-field images has become an urgent problem that needs to be addressed. Digital watermarking can effectively protect the copyright ownership of light-field images. Currently, there exists no light-field image watermarking scheme that can resist various geometric attacks. In this work, relying on geranion theory and polar harmonic Fourier moments (PHFMs), geranion polar harmonic Fourier moments (GPHFMs) are constructed and utilized for light-field image watermarking. The geranion represents a hypercomplex number containing one real part and thirty-one imaginary parts, and the imaginary parts of geranion can be used to encode multiple image color components while maintaining the correlation between each component. GPHFMs are stable image features, with good image reconstruction ability and stability. Essentially, the light-field image watermarking based on GPHFMs offers good imperceptibility and robustness, can resist various attacks, and effectively solves the problem of current watermarking schemes related to their inability of resisting geometric attacks. Furthermore, it is verified through experiments that the proposed scheme is more robust than the previously reported schemes.

Bit level color image encryption using Logistic-Sine-Tent-Chebyshev (LSTC) map

The paper presents a bit-level chaos based color image encryption technique using Logistic-Sine-Tent-Chebyshev (LSTC) map. The color image is first decomposed into red, blue, and green color image components. Each color image component is transformed to an 8-bit binary plane. Mutual diffusion of two sequences is used to scramble two binary elements using the LSTC map, cyclic shifts, and the XOR operation. The binary element confusion is performed using a chaos map and transformed into binary bit planes. With the help of the chaos map, the binary element is swapped and transformed into another binary bit plane. Individual cipher text image components are obtained by combining the binary bit planes. Finally, the encrypted image component is combined to generate the color cipher text image. The proposed scheme experimental results show excellent resistance to statistical attack, differential attack, and brute-force attack with a single round of encryption. As a result, the proposed scheme is secure and reliable for transmitting color images over the internet.

Secure audio signal transmission based on color image watermarking

AbstractThis paper presents a new color image watermarking system with encrypted audio signals using singular value decomposition (SVD), Arnold, and chaotic techniques for secure audio transmission over open channels. This system is based on embedding encrypted audio watermarks after transforming them into a 2‐D format in the singular values of the color cover image components. Three different audio watermarks are embedded in the three color image components after separating the cover image into its red, green and blue components. The three resulting watermarked components are merged again to produce the final color watermarked image. To maintain the audio signal quality, we estimate some audio signal quality metrics after converting the audio signal into a 1‐D format. The transformation from the 1‐D to 2‐D formats is performed through lexicographic ordering. Simulation results demonstrate that the proposed system preserves the high quality of the RGB cover image. In addition, the audio watermark extraction and decryption are possible, even in the presence of attacks. Furthermore, the results show an enhancement in the watermark detectability in the presence of severe attacks, such as rotation, blurring, cropping, histogram equalization, and noise addition to the watermarked images.

A robust and multi chaotic DNA image encryption with pixel-value pseudorandom substitution scheme

A color image DNA encryption system, based on multi optical chaos and pixel-value pseudorandom substitution, is proposed. In the scheme, four twin-slave-laser-pairs (TSLPs) subject to the optical injection from the chaotic master laser (ML) generate the four respectively synchronized chaotic signals. Three of these signals are used to generate keys, which are performed DNA operations with three components of color image, and the rest chaotic signals are utilized to control the choice of styles of DNA operations. The proposed image encryption algorithm includes pixel-value pseudorandom substitution based on global bit scrambling and image diffusion based on DNA encryption. After the group velocity dispersion (GVD) inside 50 km long SMF is compensated by a 1 km long DCF, the data can be well recovered at receiving end. The research results highlight that our cipher system can well achieve the encryption and decryption of color image, and is effective and highly secure to resist a variety of attacks by analyzing the randomness, key sensitivity, statistical feature, information entropy, differential performance, noise effect, PSNR and MSE of image in encryption and decryption process. The scheme is promising for color image encryption application in optical communication.

Color image analysis with novel trinion decimal-order polar harmonic transforms

Polar harmonic transforms (PHTs) are a kind of continuous orthogonal moments (COMs) that have excellent image description capability. To improve the anti-noise and reconstruction performance of PHTs, integer-order PHTs are generalized to order by a set of novel decimal-order polar harmonic transforms (DPHTs). On this basis, in combination with trinion theory, the DPHTs are extended to trinion decimal-order polar harmonic transforms (TDPHTs) applicable to color images. The color image is processed as a whole, and the internal relations among three components of color images are fully reserved and utilized. Compared with quaternion color image processing, trinion color image processing effectively avoids information redundancy and improves computational efficiency. Color image reconstruction and zero-watermarking algorithm experiments show that TDPHTs have excellent color image description ability and robustness.

Image Encryption and Authentication With Elliptic Curve Cryptography and Multidimensional Chaotic Maps

Many researchers have used the properties of the popular Elliptic Curve Cryptography(ECC) to devise a stronger and faster image encryption algorithm to assure the secrecy of images during online transmission. In this paper, a robust Elliptic curve based image encryption and authentication model for both grayscale and color images has been proposed. The model uses the secure Elliptic Curve Diffie-Hellman(ECDH) key exchange to compute a shared session key along with the improved ElGamal encoding scheme. 3D and 4D Arnold Cat maps are used to effectively scramble and transform the values of plain image pixels. A well-structured digital signature is used to verify the authenticity of the encrypted image prior to decryption. The model produces good-quality cipher images with an average entropy of 7.9993 for grayscale and 7.99925 for the individual components of color images. The model has high average NPCR of 99.6%, average UACI of 33.3% and low correlation for both grayscale and color images. The model has low computational costs with minimized point multiplication operations. The proposed model is robust with high resilience against statistical, differential, chosen-plaintext(CPA), known-plaintext(KPA) and occlusion attacks.

QR code based color image stego-crypto technique using dynamic bit replacement and logistic map

This paper uses a novel color image stego-crypto technique to enhance the capacity, security and robustness of data embedding process. The proposed scheme uses a base64 encoding technique and along with QR code generator to transform the secret data, i.e., watermark to a 2D binary matrix, i.e., QR code that considered as a first-level encryption process. Followed by, embedding of individual QR code into the color image components, namely red, green and blue using a dynamic bit replacement technique that guarantees a second level of security. Subsequently, scrambling of random block-pixels and the encryption of logistic chaos are performed. The experimental outcome of three levels of security scheme has proved to be with a much larger key space and a strong resistance to brute force, statistical and differential attacks. The correlation between adjacent pixels is observed to be uniformly distributed in the cipher image and the information entropy value is close to an ideal value of 8. From the simulation results, it is observed that the proposed security scheme has outperformed the existing standard encryption techniques within a single round of iteration in terms of security and robustness.

Hiding cipher-images generated by 2-D compressive sensing with a multi-embedding strategy

In terms of 2-D compressive sensing (CS), multi-embedding strategy and chaotic systems, a novel color image encryption scheme to generate visually meaningful cipher image is proposed in this paper. Firstly, red, green and blue components of color image are compressed to obtain measurement value matrices by virtue of 2-D CS, respectively. Next, the assembled measurement value matrix is shuffled in bit and pixel level and diffused to get a compressed cipher image. Subsequently, two embedding methods are presented to get visually meaningful color or grayscale cipher image by embedding cipher image into color or grayscale carrier image. Compared with volume of plain image, that of carrier image and final cipher image has reduced more than 50%. Moreover, a 4-D hyperchaotic system is applied to generate measurement matrices and control pixel-level confusion, Logistic system is utilized to control bit-level confusion and produce key matrix combined with Local Binary Pattern (LBP), and their initial values are computed by SHA 256 hash value of plain image, which enhances the relationship between plain image and encryption process. Embedding hash value into carrier image prevents extra transmission and storage. Simulation results and security analyses demonstrate the effectiveness and security of the proposed algorithm.

Image Retrieval Scheme Using Quantized Bins of Color Image Components and Adaptive Tetrolet Transform

In this paper, a three stage hierarchical image retrieval scheme using a color, texture and shape visual contents (or descriptors) is proposed, since single visual content is not produce an adequate retrieval results effectively. This scheme has reduced the searching space during the image retrieval process at a certain extent due to the hierarchical mode. In initial stage, the shape feature descriptor has been computed by simple fusion of histograms of gradients and invariant moments of segmented image planes. The shape based retrieval process has reduced the search space by discarding the non-relevant images from the universal dataset (or original dataset) effectively and kept the retrieved images into the intermediate dataset. In the second stage, the texture feature descriptors have been computed from the intermediate sub-image dataset by applying the adaptive tetrolet transform on image plane of preprocessed HSV color image. This transform provides the multi-resolution images with finer details by employing the tetrominoes and the proper arrangement of tetrominoes contributes the effective local geometry of image plane. The gray level co-occurrence matrix based texture feature descriptor is obtained by computing second order statistical parameters from each decomposed sub-image. At this stage, the most of the irrelevant images are discarded by retrieving the images from intermediate dataset but still some undesired images are left, those will be handled at the last stage. At this stage, fused color information is captured by applying the color autocorrelogram on both the non-uniform quantized color components of the preprocessed HSV color image. Finally, the color feature descriptor produces the desired retrieval results by discarding the irrelevant images from the texture based sub-image dataset. The proposed scheme has also low computational overhead due to the use of three descriptors at different stages separately. The retrieved results show the better accuracy as compared to the other related visual contents based image retrieval schemes.

A new image encryption algorithm with nonlinear-diffusion based on Multiple coupled map lattices

This paper proposes a new spatiotemporal chaos system named Multiple coupled map lattices (MCML). The proposed spatiotemporal chaos system has outstanding cryptographic features, which is very suitable for encryption algorithms. Based on this system, this paper proposes a new image encryption algorithm. The proposed algorithm employs the strategy of nonlinear-diffusion for the first time, and simultaneously performs shuffling and diffusion. The ciphertext value of each pixel in the diffusion phase depends on a chaotic interference value, a pixel value of the plain image, and two values of the ciphered image non-adjacent to it. This strategy reduces the correlation between adjacent pixels of the plain image as well as the correlation between the R, G and B components of color image. Theoretical analysis and experimental results prove the high efficiency and security of the proposed algorithm.

STEGANALYSIS OF DIGITAL IMAGES UNDER DIFFERENT CONTENT FULLNESS

An improvement of the steganalytic method for detection of the presence of additional information in color digital images which showed high efficiency in identifying stegano formed by embedding of secret data only into one color component of the container is presented. The proposed method analyses digital image in the spatial domain and is based on the accounting of sequential color triads in the matrix of unique colors of the digital content. However, in the process of steganographic transformation cases of embedding of confidential data into two and three color components of images are possible that ensures the concealment of a larger amount of information and requires the improvement of the existing method of steganalysis. In the course of the conducted research the character of perturbations in the quantity of sequential triads of triplets in a matrix of unique colors as a result of embedding of additional information into two and three color components of images originally stored in a losses format was analyzed. Considering obtained results the parameters of the original method for detecting of stegano was refined. It has been established that the character of changes in the quantity of sequential triads of triplets as a result of steganographic transformation is different in cases of using containers in a losses format and containers in a lossless format. Based on the obtained data the steganalytic method has been improved by integrating it with the method of detection the fact of compression of digital content developed earlier. The developed method provides high efficiency in detecting stego formed with different degree of container fullness without reducing the accuracy of identifying the filled color components if the additional information was embedded into only one color component of the digital images. This method can be used as a basis for complex steganalysis of digital contents by using existing methods that analyzes color matrixes of images separately.

Stegananalysis of digital images in conditions of varying degrees of contents fullness

An improvement of the steganalytic method for detection of the presence of additional information in color digital images which showed high efficiency in identifying stego formed by embedding of secret data only into one color component of the container is presented. The proposed method analyses digital image in the spatial domain and is based on the accounting of sequential color triads in the matrix of unique colors of the digital content. However, in the process of steganographic transformation cases of embedding of confidential data into two and three color components of images are possible that ensures the concealment of a larger amount of information and requires the improvement of the existing method of steganalysis. In the course of the conducted research the character of perturbations in the quantity of sequential triads of triplets in a matrix of unique colors as a result of embedding of additional information into two and three color components of images originally stored in a losses format was analyzed. Considering obtained results the parameters of the original method for detecting of stego was refined. It has been established that the character of changes in the quantity of sequential triads of triplets as a result of steganographic transformation is different in cases of using containers in a losses format and containers in a lossless format. Based on the obtained data the steganalytic method has been improved by integrating it with the method of detection the fact of compression of digital content developed earlier. The developed method provides high efficiency in detecting stego formed with different degree of container fullness without reducing the accuracy of identifying the filled color components if the additional information was embedded into only one color component of the digital images. This method can be used as a basis for complex steganalysis of digital contents by using existing methods that analyzes color matrixes of images separately.

Low rank tensor completion for multiway visual data

Tensor completion recovers missing entries of multiway data. Teh missing of entries could often be caused during teh data acquisition and transformation. In dis paper, we provide an overview of recent development in low rank tensor completion for estimating teh missing components of visual data, e. g. , color images and videos. First, we categorize these methods into two groups based on teh different optimization models. One optimizes factors of tensor decompositions wif predefined tensor rank. Teh other iteratively updates teh estimated tensor via minimizing teh tensor rank. Besides, we summarize teh corresponding algorithms to solve those optimization problems in details. Numerical experiments are given to demonstrate teh performance comparison when different methods are applied to color image and video processing.

QR code based color image cryptography for the secured transmission of ECG signal

The paper presents a novel QR code based color image steganography to facilitate remote transmission of ECG signal along with patient diagnosis data. The proposed system is configured with two stage security processes, namely pixel permutation and chaos encryption. A three step sequential strategy is adapted for the implementation of the system. At first, the diagnose information in the form of alphanumeric data is given to QR code generator for the generation of equivalent 2D binary matrix. Similarly, the ECG signal samples are transformed into alphanumeric cipher text by involving integer to binary sequence conversion process and eventually into corresponding QR codes. Secondly, the both diagnose data as well as ECG signal integrated QR codes are embedded within individual R, G and B color image components by using the pixel permutation process. Finally, the color image components, R, B and G are individually encrypted by using 1D chaotic encryption technique as an attempt to enhance further the security of existing steganography process. The experimental results are validated in terms of NCPR, UACI and also entropy which found to be better and comparable than other baseline algorithms.