A Review on Encryption and Decryption of Image using Canonical Transforms & Scrambling Technique

Data security is a prime objective of various researchers & organizations. Because we have to send the data from one end to another end so it is very much important for the sender that the information will reach to the authorized receiver & with minimum loss in the original data. Data security is required in various fields like banking, defence, medical etc. So our objective here is that how to secure the data. So for this purpose we have to use encryption schemes. Encryption is basically used to secure the data or information which we have to transmit or to store. Various methods for the encryption are provided by various researchers. Some of the methods are based on the random keys & some are based on the scrambling scheme. Chaotic map, logistic map, Fourier transform & Fractional Fourier transform etc. are widely used for the encryption process. Now day’s image encryption method is very popular for the encryption scheme. The information is encrypted in the form of image. The encryption is done in a format so no one can read that image. Only the person who are authenticated or have authentication keys can only read that data or information. So this work is based on the same fundamental concept. Here we use Linear Canonical Transform for the encryption process

An Experimental Approach for Encryption and Decryption of Image using Canonical Transforms & Scrambling Technique

Data security is a prime objective of various researchers & organizations. Because we have to send the data from one end to another end so it is very much important for the sender that the information will reach to the authorized receiver & with minimum loss in the original data. Data security is required in various fields like banking, defense, medical etc. So our objective here is that how to secure the data. This study is performed on MATLAB R2016b with standard databasegrey scale images like Barbara, Cameraman and Lenna or by using the personalize images in standard format. First of all, the images are scrambled and then the generation of a new complex image took place. Initially phase mask is applied on the complex image by using RPM 1, and then the complex image is encrypted by using LCT of first order. Again the phase mask RPM 2 is applied on the encrypted image followed by the LCT of second order to get the encrypted image finally. Reverse process is applied to get the original image. Various parameters are calculated which shows various aspects. Like Change in the value of MSE with change in order of transform tells the quality of encrypted image. Correlation coefficient of encrypted and decrypted image also shows the difference between the encrypted and decrypted image. The original image is then reconstructed and histogram of all these images analyzed. Robustness and imperceptibility of images increases by the proposed method

Multilayer Security of RGB Image in Discrete Hartley Domain

In this article, we present RGB image encryption and decryption using random matrix affine cipher (RMAC) associated with discrete Hartley transform (DHT) and random matrix shift cipher (RMSC). The parameters in RMAC and RMSC phases act as two series of secret keys whose arrangement is imperative in the proposed algorithm. The computer simulations with results and examples are given to analyze the efficiency of the proposed approach. Further, security analysis and comparison with the prior techniques successfully supports the robustness and validation of the proposed technique

Multiple-image encryption by compressive holography

We present multiple-image encryption (MIE) based on compressive holography. In the encryption, a holographic technique is employed to record multiple images simultaneously to form a hologram. The two-dimensional Fourier data of the hologram are then compressed by nonuniform sampling, which gives rise to compressive encryption. Decryption of individual images is cast into a minimization problem. The minimization retains the sparsity of recovered images in the wavelet basis. Meanwhile, total variation regularization is used to preserve edges in the reconstruction. Experiments have been conducted using holograms acquired by optical scanning holography as an example. Computer simulations of multiple images are subsequently demonstrated to illustrate the feasibility of the MIE scheme.published_or_final_versio