A Chaos Based Image Encryption in Transform Domain

A Chaos Based Image Encryption in Transform Domain

Lucky Yadava, Prof. Virendra Vermab

Abstract: Off late conventional image data hiding and encryption mechanisms have seen a shift towards homomorphic images which can be thought of being created from a constant illumination and a varying reflectance. In this proposed work, the Fresnel Transform is employed to convert normal images into homomorphic images to reduce the redundancy of images. Subsequently, the image is converted to the transform domain using the 4th level Discrete Wavelet Transform. The truncation of the DWT is done at the 4th level so as to limit the complexity of the system. Once the image is converted to the transform domain, it is encrypted using the Chaotic Baker Map. The embedded data can be extracted from the encrypted domain itself without the mandatory necessity of first decrypting the image thereby making the secret image extraction faster and less perceptible. The evaluation of the proposed technique is done based on the histogram analysis, the MSE, PSNR, Correlation and Entropy. It has been shown that the proposed system performs better compared to the previously existing technique in terms of the PSNR for the same image from the benchmark USC-SIPI image dataset.

Keywords: Data Hiding, Homomorphic Images, Fresnel Transform, Discrete Wavelet Transform, Chaotic Baker Maps, PSNR