Image Watermarking with DCT-Optimization based Psychovisual Threshold and Fuzzy Adaptive Median Filtering (FAMF) for Noise Distortion

Abstract

The high speed development of internet technology, illegal copy, transmission and distribution of digital multimedia has emerged to be a significant security challenge. This challenge inspires the design of a solution for image authentication and copyright protection. Recently, an optimal Discrete Cosine Transform (DCT) psychovisual threshold is proposed for digital watermarking approach. The newly introduced approach also yields a distorted watermark extraction with image-rotation attack. This problem will be focused in this research work. In order to resolve this issue, Fuzzy Adaptive Median Filtering (FAMF) is introduced for noise elimination in the distorted watermark extraction suffering from image-rotation attack. In the newly introduced work, embedding regions are decided on the basis of the lowest modified entropy value of the image blocks. In this, the optimization of the lowest modified entropy value is done by using Bat Algorithm (BA). Therefore, the optimal psychovisual threshold is decided for embedding the watermark in the host image for getting a better image quality. The lowest modified entropy value specified the greatest redundant image information. The scrambling of the watermark bits are done prior to them being embedded into the chosen coefficients. The newly introduced approach has been tested under various kinds of attacks. The newly introduced approach also exhibits the superior performance in terms of reliability under several numbers of combined attacks.