Image Encrypted Using Circular Map, Block Compressed Sensing and Hyper GWO-COOT Optimization

For secure image communications, the Internet must be shielded against unauthorized acquisition or malevolent access.The need for image encryption methods with enough capacity and good efficiency is growing due to the current situation.The purpose of this research work is to solve the problems in today's communication security using a proposed image encryption algorithm.The proposed image encryption system includes the combination of a chaotic system, compressive sensing and Hyper optimization algorithm.The initial values of chaos are extracted using the SHA512.Discrete Wavelet Transform (DWT) is applied to sparse image pixels.The image is shuffled using a FAN transform with a circular map.Next, the image is divided into blocks to facilitate the application of block compressive sensing that utilized the Hadamard measurement matrix.These blocks are masked as one part to quantify the pixels.The logistic map is improved by a hybrid transform which is the combination of Discrete Cosine Transform, Arnold Transform and Discrete Wavelet Transform (CAW).The image is finally scrambled using a Circular Map with a Hyper Optimization that combines two meta-heuristics algorithms namely GWO and COOT.According to simulation experiment findings and security assessments, the algorithm was extremely resilient to differential, statistical, and interference assaults.Based on the experimental results, it was found that the average rate of PSNR was 33.8189, the rate of entropy was 7.99454, the average rate of SSIM was 0.96144, the rate of UACI was 99.62892 and the average rate of NPCI was 33.50304.The results showed that it is an effective method of encryption and strong enough against various types of attacks.