Discrete Wavelet Transform with Adaptive Network-Based Fuzzy Inference System for Compression of Images

Abstract

Image Encryption has a significant role to play in different fields like information security.Images are encryptedfor various purposes. Compression refers to the process that is carried out once the encryption is completed. In this review work, a hybrid technique has been followed for image encryption and decryption. First, input images are sent for preprocessing employing the median filter with the aim of removing the noise that is regarded to be unnecessary. This elimination process aids in improving the quality of the particular image. So the denoised image can be divided into different segments with the goal of encrypting the various blocks of images. This way, the required and unwanted blocks can be found during this above mentioned process. Encryption technique would follow Hybrid Chaos along with Discrete Cosine Transform shortly known as DCT. The encrypted image is then compressed with the help of Discrete Wavelet Transform (DWT) With Adaptive Network-Based Fuzzy Inference System (ANFIS). The experimental results indicate that the newly introduced DWT-ANFIS based compression attains a better performance in comparison with the availablecompression approaches in terms of Compression Ratio (CR) and Peak-Signal-Noise-Ratio (PSNR).