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This article introduces a fast meshless algorithm for the numerical solution nonlinear partial differential equations (PDE) by Radial Basis Functions (RBFs) approximation connected with the Total Variation (TV)-based minimization functional and to show its application to image denoising containing multiplicative noise. These capabilities used within the proposed algorithm have not only the quality of image denoising, edge preservation but also the property of minimization of staircase effect which results in blocky effects in the images. It is worth mentioning that the recommended method can be easily employed for nonlinear problems due to the lack of dependence on a mesh or integration procedure. The numerical investigations and corresponding examples prove the effectiveness of the recommended algorithm regarding the robustness and visual improvement as well as peak-signal-to-noise ratio (PSNR), signal-to-noise ratio (SNR), and structural similarity index (SSIM) corresponded to the current conventional TV-based schemes. [ABSTRACT FROM AUTHOR]

Cryptography and steganography are two important and related fields of information security. But, steganography is slightly different in the sense that it hides the existence of secret information from unauthorized users. It is one of the most appealing research domains, have applications like copyright protection, data integrity protection and manipulation detection. Several steganography techniques have been proposed in literature. But, in this work a new information hiding algorithm is presented. The proposed technique de-correlates frequency components of cover image using discrete cosine transform and uses the least significant bits of frequency components for hiding secret information. The tech-nique hides variable number of bits of secret message in different frequency components. Therefore, it hides different amount of secret information in different regions of cover im-age and results in enhancement of security. The algorithm has the flexibility to change the hiding capacity and quality of final stego image. It has been observed from experimental results that a hiding a capacity from 3% to 43% can be achieved with significantly good quality of 41 dB to 37 dB in term of peak signal to noise ratio. The successful recovery of the hidden information need the pattern, called stego key, in which is used in hiding process. The algorithm provides twofold security; hiding keeps the existence of hidden information secret and the large key size makes the retrieval of hidden information difficult for intruders. [ABSTRACT FROM AUTHOR]

This work presents an asymmetric data hiding method using binary patterns detected with a metaheuristic algorithm. The technique uses a pheromone matrix and two stage decision process to detect binary patterns. The binary pattern acts as a secret key to isolate the complex area of the cover image from the smooth area, both the process of information hiding and information retrieval. The method hides confidential data in the complex area of cover media using the information present in the detected binary pattern and leaves the smooth area's pixel unaffected. The confidential data is hidden asymmetrically, and the asymmetry is ensured using a stego key of varying configuration and size. The binary pattern, stego key, and asymmetry of the number of bits hidden in the cover image's pixels enhance the security of confidential data by many folds. The visual analysis of the results demonstrated that the presented technique does not add any detectable modification to the resulting images and keeps the hidden data innocent for observers. The quantitative results obtained in terms of the evaluation metrics of peak signal to noise ratio, mean square error, structure similarity index, and hiding capacity, show that the proposed technique has a high value of peak signal to noise ratio and structural similarity index with a significant hiding capacity, while the mean square error is also significantly low. The high security and the quality of resulting images make it impossible for unauthorized users to obtain hidden information. Hence, the existence of confidential information is not compromised. Moreover, the comparative analysis shows that the performance of the presented technique, in terms of the evaluation metrics, is better than or comparable with state-of-the-art techniques. The binary pattern, large size, and large variety of the stego key make the proposed technique superior to the state-of-the-art techniques, in terms of security. [ABSTRACT FROM AUTHOR]

This paper presents a new enhanced stego block chaining (ESBC) technique for data hiding to address the bandwidth and transmission time issues of simple stego block chaining (SBC). In simple SBC data hiding method, the security of the hidden information is increased by increasing the number of stages, but the addition of each stage decreases the hiding capacity. This increases the size of the data needed to transmit the secret message and thus results in an increase in the required bandwidth and transmission time. The proposed ESBC technique addresses the bandwidth and transmission time issues of the simple SBC method. The output of the ESBC is a high quality stego image with peak signal-to-noise ratio above 40 dB and provides the same additional security as simple SBC but reduces the requirements of the bandwidth and transmission time by one half of that of the simple SBC and, thus, solves the hiding capacity issues of SBC for low bandwidth channels. Copyright © 2017 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

The super-resolution (SR) technique reconstructs a high-resolution image from single or multiple low-resolution images. SR has gained much attention over the past decade, as it has significant applications in our daily life. This paper provides a new technique of a single image super-resolution on true colored images. The key idea is to obtain the super-resolved image from observed low-resolution images. A proposed technique is based on both the wavelet and spatial domain-based algorithms by exploiting the advantages of both of the algorithms. A back projection with an iterative method is implemented to minimize the reconstruction error and for noise removal wavelet-based de-noising method is used. Previously, this technique has been followed for the grayscale images. In this proposed algorithm, the colored images are taken into account for super-resolution. The results of the proposed method have been examined both subjectively by observation of the results visually and objectively by considering the peak signal-to-noise ratio (PSNR) and mean squared error (MSE), which gives significant results and visually better in quality from the bi-cubic interpolation technique. [ABSTRACT FROM AUTHOR]