Pixel Substitution Research Articles

A new chaos based color image encryption algorithm using permutation substitution and Boolean operation

A new color image encryption algorithm is proposed by using chaotic maps. Cipher image is constructed in three phases. In the first phase permutation of digital image is performed with the help of a chaotic map. The second phase uses chaotic substitution box for pixel substitution and finally in the third phase a Boolean operator XOR is used for mixing chaotic logistic based random sequence. Chaotic maps have main role in this encryption. Chaos theory, due to its randomness and unpredictable behaviors, is known as favorite for the purpose of image encryption. The RGB components of image scrambled by permutation-substitution and Boolean operation, show good results for security and performance analysis. Different tests of security analysis like key space, key sensitivity, correlation analysis, entropy, histogram analysis, number of pixel change rate (NPCR) and unified average changing intensity (UACI) tests are employed on the proposed scheme. On the basis of these tests, we believe that proposed scheme is well suited for practical applications.

Fast and Secure Medical Image Encryption Based on Non Linear 4D Logistic Map and DNA Sequences (NL4DLM_DNA).

This paper proposes an innovative image cryptosystem algorithm using the properties of the block encryption, 4D logistic map and DNA systems. Multiple key sequences are generated and pixel substitution is performed by using nonlinear 4D logistic map, then encryption is performed by using DNA rules to ensure that the different blocks are encrypted securely. The results of the experiment indicate that the proposed Non Linear 4D Logistic Map and DNA (NL4DLM_DNA) sequence based algorithm gives better performance, which is analyzed on the basis of security, quality, attack resilience, diffusion and running time as compared to some previous works.

Homogenized Chebyshev-Arnold Map and its Application to Color Image Encryption

In this paper, we propose a homogenized Chebyshev-Arnold map (HCAM) by homogenizing the linear coupling of Chebyshev map and Arnold map. The proposed HCAM has complex dynamical behaviors and can avoid the problems of the original Chebyshev map when used in image encryption. Based on the HCAM, we present a color image encryption algorithm that contains confusion and diffusion processes. In the confusion stage, we use the random chaotic matrix transform (RCMT) to randomize the shifting steps, which can eliminate the regular pattern of the original CMT and enhance the security level. In the diffusion stage, we use a SHA-512- and SHA-384-based fast pixel substitution scheme to perform the bit-level exclusive-or operation, which can obtain outstanding self-adaptiveness and high efficiency. The experimental results and security analysis demonstrate that the proposed algorithm has high level of security and robust to the potential attacks.

A Novel Quasigroup Substitution Scheme for Chaos Based Image Encryption

A During last two decades, there has been a prolific growth in the chaos based image encryption algorithms. Up to an extent these algorithms have been able to provide an alternative to exchange large media files (images and videos) over the networks in a secure way. However, there have been some issues with the implementation of chaos based image ciphers in practice. One of them is reduced/small key space due to the fact that chaotic behavior is only observed for certain range of system parameters/initial conditions of the chaotic system used in such algorithms. To overcome this difficulty, we propose a simple, efficient and robust image encryption algorithm based on combined applications of quasigroups and chaotic standard map. The proposed image cipher is based on the popular substitution-diffusion architecture (Shanon) where a quasigroup of order 256 and chaotic standard map have been used for the substitution and permutation of image pixels respectively. Due to the introduction of quasigroup as part of the secret key along with the parameter and initial conditions of the chaotic standard map, the key space has been increased significantly. The proposed image cipher is very fast due to the fact that the substitution based on the quasigroup operations is very simple and can be executed easily through the lookup table operations on Latin squares (which are Cayley operation tables of quasigroups) and the permutation is performed row-by-row as well as column-by-column using the pseudo random number sequences gener-ated through the chaotic standard map. The security and performance have been analyzed through the histograms, correlation coefficients, information entropy, key sensitivity analysis, differential analysis, key space analysis etc. and the results prove the efficiency and robustness of the proposed image cipher against the possible security threats.

Large-Area Gap Filling of Landsat Reflectance Time Series by Spectral-Angle-Mapper Based Spatio-Temporal Similarity (SAMSTS)

Landsat time series commonly contain missing observations, i.e., gaps, due to the orbit and sensing geometry, data acquisition strategy, and cloud contamination. A spectral-angle-mapper (SAM) based spatio-temporal similarity (SAMSTS) gap-filling algorithm is presented that is designed to fill small and large area gaps in Landsat data, using one year or less of data and without using other satellite data. Each gap pixel is filled by an alternative similar pixel that is located in a non-missing region of the image. The alternative similar pixel locations are identified by comparison of reflectance time series using a SAM metric revised to be adaptive to missing observations. A time series segmentation-and-clustering approach is used to increase the search efficiency. The SAMSTS algorithm is demonstrated using six months of Landsat 8 Operational Land Imager (OLI) reflectance time series over three 150 × 150 km (5000 × 5000 30 m pixels) areas in California, Minnesota and Kansas. The three areas contain different land cover types, especially crops that have different phenology and abrupt changes due to agricultural harvesting, which make gap filling challenging. Fillings on simulated gaps, which are equivalent to 36% of 5000 × 5000 images in each test area, are presented. The gap filling accuracy is assessed quantitatively, and the SAMSTS algorithm is shown to perform better than the simple closest temporal pixel substitution gap filling approach and the sinusoidal harmonic model-based gap filling approach. The SAMSTS algorithm provides gap-filled data with five-band reflective-wavelength root-mean-square differences less the 0.02, which is comparable to the OLI reflectance calibration accuracy.

An efficient mixed inter-intra pixels substitution at 2bits-level for image encryption technique using DNA and chaos

In this paper, an image encryption system is proposed that uses only addition operation to achieve higher efficiency at diffusion phase after DNA encoding at pixel level. The image is first permuted and then encoded into DNA bases using sub-set of DNA complementary rules chaotically. Afterwards, the adjacent columns of DNA encoded image are added in the substitution phase named as inter-intra pixels substitution which followed by row addition named as inter-pixels substitution. This substitution is performed by adding DNA bases where each DNA base is composed of 2-bits. The addition operation performs randomly between DNA bases named mixed inter-intra pixel substitution. To strengthen security, initial conditions for chaotic maps are computed from SHA-256 hash of plain image which leads to enhance the resistance against known/chosen-plaintext and differential attacks. Due to fewer computational operations, the efficiency of the proposed cipher is high. The simulated results show that the proposed technique is extremely robust against statistical and differential attacks. It successfully surpassed the statistical tests such as Histogram, Correlation, Chi-Square and Entropy. For differential attack, it passed quantitative as well as qualitative Number of Pixel Change Rate (NPCR) and Unified Average Cipher Intensity (UACI) tests in a single round of encryption.

Hybrid Image Encryption Technique to Improve the Security Level by using (n, k, p) Gray Code and XOR Operation

Objectives: To enhance the performance of decomposition encryption methods, a modified image encryption technique is utilized in (n, k, p) Gray coding exhibit the application of (n, k, p) Gray coding in the encryption of images. Methods/ Statistical Analysis: We proposed a revised algorithm based on image encryption that improves the level of security for available (n, k, p) based bit plane decomposition encryption technique. The proposed hybrid methods starts with bit-plane decomposition of (n, k, p) Gray coding then shuffling each bit plane using random scrambling finally pixel substitution based on X-OR Operation. Findings: The experimental results and comparison demonstrates that proposed encryption algorithm have best performance in image encryption. Applications/Improvements: This algorithm could be utilized for securing protection in biological traits, imaging systems in medical field and digital video surveillance system. Our next plan will additionally enhance and examine the execution of (n, k, p)-Gray coding for data hiding and picture de-noising. Keywords: Bit-Plane Decomposition, Image Encryption, (n, k, p)-Gray Code, Pixel Permutation, X-OR

A novel algorithm for bad pixel detection and correction to improve quality and stability of geometric measurements

An algorithm for detection and individually substitution of bad pixels for further restoration of an image in the presence of such outliers without altering overall image texture is presented. This work presents three phases concerning image processing: bad pixel identification and mapping by means of linear regression and the coefficient of determination of the pixel output as a function of exposure time, local correction of the linear and angular coefficients of the outlier pixels based on their neighbourhood and, finally, image restoration. Simulation and experimental data were used as means of code benchmarking, showing satisfactory results.

Automatic Delineation of Clouds and Their Shadows in Landsat and CBERS (HRCC) Data

The presence of clouds and their shadows is an obvious problem for maps obtained from multispectral images. As a matter of fact, clouds and their shadows create occluded and obscured areas, hence information gaps that need to be filled. The usual approach—pixel substitution—requires first to recognize the cloud/shadow pixels. This work presents a cloud/shadow delineation algorithm, the cloud/shadow delineation tool (CSDT) designed for Landsat and CBERS medium resolution multispectral data. The algorithm uses a set of literature indices, as well as a set of mathematical operations on the spectral bands, in order to enhance the visibility of the cloud/shadow objects. The performance of CSDT was tested on a set of scenes from the Landsat and CBERS catalogues. The obtained results showed more accurate and stable performance on Landsat data. In order to validate the proposed approach, this work presents also a comparison with the F-mask algorithm on Landsat scenes. Results show that the F-mask technique tends to overestimate the cloud cover, while CSDT slightly underestimates it. However, accuracy measures show a significantly better performance of the proposed method than the F-mask algorithm in our investigation.

Improved Encryption Algorithm of Images Based on Three-Dimensional Chaos

It describes an improved encryption algorithm of a three-dimensional image based on multiple chaotic systems. The algorithm uses a variety of chaotic encryption system to cut the image into three-dimensional matrix systems, in three-dimensional space do the image scrambling transformation, three-dimensional chaotic sequence output by multiple chaotic systems achieved three color pixel substitution transformation of the spatial color image. Finally, according to the theoretical analysis and simulation results it shows that the encryption algorithm with large key space, good confidentiality, and the pixel values of the encryption image has a random uniform distribution features and zero correlation of the neighboring pixel values, verifies the proposed scheme has high security.

Curvature preserving image super-resolution with gradient-consistency-anisotropic-regularization prior

Single image super-resolution (SR) often suffers from annoying interpolation artifacts such as blur, jagged edges, and ringing. In this paper, we aim to achieve artifact-free SR reconstruction from an input low resolution (LR) image using adaptive de-convolution and curvature refinement. To achieve this, we propose a curvature preserving image SR method based on a gradient-consistency-anisotropic-regularization (GCAR) prior. The gradient consistency term effectively suppresses visual artifacts such as ringing and preserves sharp edges in images while the anisotropic regularization term adaptively preserves the high frequency information according to the gradient magnitude. The complementary two terms are elaborately combined into the GCAR prior for the SR reconstruction. The GCAR prior is very effective in preserving image details and recovering high frequency information. Moreover, we use curvature refinement to remove jagged artifacts caused by aliasing due to decimation. The proposed method employs an effective feedback-control loop which contains adaptive de-convolution, re-convolution, pixel substitution, and curvature refinement. The GCAR prior is utilized in the adaptive de-convolution step. Extensive experiments on various test images demonstrate that the proposed method produces natural-looking and artifact-free SR results in terms of both visual quality and quantitative performance.

A new secure and sensitive image encryption scheme based on new substitution with chaotic function

In this paper, a new image encryption scheme is proposed with high sensitivity to the plain image. In proposed scheme, two chaotic functions and logical operator xor are used. Image encryption process includes substitution of pixels and permutation. Using the new method of substitution, algorithm sensitivity somewhat has elevated to changes in the plain image that by changing a single pixel of the plain image, amount of NPCR reaches 100 %. Results of tests show that the cipher image does not give any information of statistical such as entropy, histogram and correlation of adjacent pixels to attackers. Also the proposed scheme has the wide key space and is so safe to the noise ratio and compression.

A New Image Scrambling Scheme through Chaotic Permutation and Geometric Grid based Noise Induction

Digital images cover the major portion of data that is being exchanged over communication network. When digital images are personal or confidential a high level security has to be provided. Traditional Encryption which is normally used to disguise data making it unintelligible to unauthorized observers do not consider the inherent features of images and thus is not considered to be highly effective with regard to computational complexity and also the security level enforced on images. This paper presents a new concept for image scrambling by applying pixel permutation and pixel substitution on an image split into irregular trapezoidal grids. Pixel permutation is performed using Arnold’s 2-D cat map which will disarray the pixels. Then substitution is performed employing a distinctive feature that the key for substitution process for pixels are derived from the properties of the trapezoidal grid to which the pixel belongs. Thus pixels mapped to various grids will have different noise induction thus providing high level security. The entire process of pixel permutation and substitution is repeated for several iterations to provide higher level security. The experimental results show that the proposed algorithm can successfully scramble the images, and the security analysis of the algorithm also demonstrates that the proposed scheme can withstand various cryptanalytic and statistical attacks. General Terms Security, Image Processing, Chaos Theory.

An Enhanced Data Hiding Approach using Pixel Mapping Method with Optimal Substitution Approach

Data Hiding is one of the challenging issues in the field of Network Security. Unlike cryptography, Steganography is used to hide the existence of secret message by embedding the message behind any cover object like image, text, audio, video files. Various authors proposed, various methods for hiding secret information behind gray scale images such as least significant method, gray level modification, pixel value differencing, pixel mapping method and pixel mapping method with BPCS, but all these method are not up to the marks that means increasing the embedding capacity of StegoImage and to provide Stego-Image with an imperceptible quality are still challenges. To get better imperceptible quality, we proposed an enhanced technique “An Enhanced Data Hiding Approach Using Pixel Mapping Method (PMM) With Optimal Pixel Substitution Approach ” that provides a better Peak Signal to noise ratio(PSNR) between Cover-Image and Stego-Image with good embedding capacity. The proposed approach is based on four modules – mapping rules, set classifier method, pixel selection method, and minimum differencing function to hide data within an image. This method works by selecting a set of pixels; map secret data into these selected pixels according to mapping rules and produces new Stego pixel value after mapping secret message according to Minimum Pixel Difference function. This integrated proposed approach provides more security to secret data as without knowing the mapping rules and locations of pixels no one could extract the secret data. This proposed approach not only provides larger embedding capacity but also produces an acceptable Stego image quality that can be seen by human eyes.

Chaotic S-Box Based Pixel Substituting for Image Encryption

This paper aims to develop an image encryption method based on the S-Box concept of advanced encryption standard (AES) and the application of chaotic system. Variable elements of the chaotic system initially generate chaotic-sub-box (CSB) and chaotic-sub-pathway (CSP) matrices, which then substitute the pixels of the original image. Map and gray-level values between the original and encrypted images indicate no interrelation after substitution, so decryption of bits, pixels, and keys even by exhaustive attack is prevented. Practical application shows that the encrypted image has 100% pixel substitution, and no image distortion occurs after image decryption. Therefore, the proposed encryption method is secure, reliable, and feasible.

A Self-Adaptive Parallel Encryption Algorithm Based on Discrete 2D-Logistic Map

A self-adaptive parallel encryption algorithm based on discrete 2D-Logistic map is developed according to the position scrambling and diffusion of multi-direction in variable space of spatial chaos. The binary sequences b1b2b3···bn are obtained according to the user key, in which the binary sequence 0 and 1 denote distribution mode of processors and the number of binary sequence n denotes cycle number. Then the pseudorandom 2D matrix is generated by 2D-Logistic map, and adaptive segmentation is applied in image matrix and pseudorandom matrix according to the value and the number of binary sequence. The parallel operation is used among blocks to improve efficiency and meet real-time demand in transmission processes. However, the pixel permutation is applied in partitioned matrix through ergodic matrix generated by pseudo-random matrix-block to decrease the correlation of adjacent pixels. Then the pixel substitution is used for fully diffusing through cipher block chaining mode until n cycles. The proposed algorithm can meet the three requirements of parallel operation in image encryption and the real-time requirement in transmission processes. The security is proved by theoretical analysis and simulation results.

Chaotic image encryption system using phase-magnitude transformation and pixel substitution

We proposed an algorithm to encrypt an image in hybrid domain, frequency and time domains. The proposed method is a private key encryption system with two main units, chaotic phase-magnitude transformation unit and chaotic pixel substitution unit. Chaotic phase-magnitude transformation unit works in frequency domain and a 2-D DFT is performed on the plain image to change the domain. A chaotic function, the tent map, is used to generate the pseudo random image, which are combined with the plain image in frequency domain. Chaotic pixel substitution unit works in time domain Bernoulli map is applied to produce another pseudo random image that is mixing with the encrypted image nonlinearly. The performance of the proposed chaotic image encryption system is analysed using a computer simulation. The distribution of histogram of encrypted image is uniform. Chi-square value for encrypted image of our proposed method is considerably low. The MSE of the proposed encrypted image is big enough. The correlation coefficients of the proposed encrypted image in all three directions are sufficiently small. The total key length is large enough to resist the proposed system against any brute-force attack. The proposed scheme is robust against chosen plaintext attacks too. The proposed chaotic image encryption system, which is used frequency and time domain together, is more secure than most of single domain image encryption systems.

Generation and evaluation of gross primary productivity using Landsat data through blending with MODIS data

Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) has been used for the blending of Landsat and MODIS data. Specifically, the 30m Landsat-7 ETM+ (Enhanced Thematic Mapper plus) surface reflectance was predicted for a period of 10 years (2000–2009) as the product of observed ETM+ and MODIS surface reflectance (MOD09A1) on the predicted and observed ETM+ dates. A pixel based analysis for six observed ETM+ dates covering winter and summer crops showed that the prediction method was more accurate for NIR band (mean r2=0.71, p≤0.01) compared to green band (mean r2=0.53; p≤0.01). A recently proposed chlorophyll index (CI), which involves NIR and green spectral bands, was used to retrieve gross primary productivity (GPP) as the product of CI and photosynthetic active radiation (PAR). The regression analysis of GPP derived from closet observed and synthetic ETM+ showed a good agreement (r2=0.85, p≤0.01 and r2=0.86, p≤0.01) for wheat and sugarcane crops, respectively. The difference between the GPP derived from synthetic and observed ETM+ (prediction residual) was compared with the difference in GPP values from observed ETM+ on the two dates (temporal residual). The prediction residuals (mean value of 1.97gC/m2 in 8 days) was found to be significantly lower than the temporal residuals (mean value of 4.46gC/m2 in 8 days) that correspondence to 12% and 27%, respectively, of GPP values (mean value of 16.53gC/m2 in 8 days) from observed ETM+ data, implying that the prediction method was better than temporal pixel substitution. Investigating the trend in synthetic ETM+ GPP values over a growing season revealed that phenological patterns were well captured for wheat and sugarcane crops. A direct comparison between the GPP values derived from MODIS and synthetic ETM+ data showed a good consistency of the temporal dynamics but a systematic error that can be read as bias (MODIS GPP over estimation). Further, the regression analysis between observed evapotranspiration and synthetic ETM+ GPP showed good agreement (r2=0.66, p≤0.01).

A New Switching-Based Median Filtering Scheme and Algorithm for Removal of High-Density Salt and Pepper Noise in Images

A new switching-based median filtering scheme for restoration of images that are highly corrupted by salt and pepper noise is proposed. An algorithm based on the scheme is developed. The new scheme introduces the concept of substitution of noisy pixels by linear prediction prior to estimation. A novel simplified linear predictor is developed for this purpose. The objective of the scheme and algorithm is the removal of high-density salt and pepper noise in images. The new algorithm shows significantly better image quality with good PSNR, reduced MSE, good edge preservation, and reduced streaking. The good performance is achieved with reduced computational complexity. A comparison of the performance is made with several existing algorithms in terms of visual and quantitative results. The performance of the proposed scheme and algorithm is demonstrated.

Chaotic Image Encryption Design Using Tompkins‐Paige Algorithm

In this paper, we have presented a new permutation‐substitution image encryption architecture using chaotic maps and Tompkins‐Paige algorithm. The proposed encryption system includes two major parts, chaotic pixels permutation and chaotic pixels substitution. A logistic map is used to generate a bit sequence, which is used to generate pseudorandom numbers in Tompkins‐Paige algorithm, in 2D permutation phase. Pixel substitution phase includes two process, the tent pseudorandom image (TPRI) generator and modulo addition operation. All parts of the proposed chaotic encryption system are simulated. Uniformity of the histogram of the proposed encrypted image is justified using the chi‐square test, which is less than χ2(255, 0.05). The vertical, horizontal, and diagonal correlation coefficients, as well as their average and RMS values for the proposed encrypted image are calculated that is about 13% less than previous researches. To quantify the difference between the encrypted image and the corresponding plain‐image, three measures are used. These are MAE, NPCR, and UACI, which are improved in our proposed system considerably. NPCR of our proposed system is exactly the ideal value of this criterion. The key space of our proposed method is large enough to protect the system against any Brute‐force and statistical attacks.