A Novel Approach to Image Hashing Based on Discrete Wavelet Transform and MATLAB Implementation

Abstract

This paper presents a novel approach to image hashing using Discrete Wavelet Transform (DWT) and MATLAB, designed to improve the robustness, accuracy, and efficiency of image-based content authentication and retrieval. Image hashing plays a critical role in applications where identifying or verifying image content is essential, such as digital watermarking, image retrieval, and copyright protection. Traditional hashing techniques often face challenges in maintaining robustness against image distortions, such as scaling, rotation, and noise. In our proposed method, DWT is employed to decompose the image into sub-bands, from which distinctive features are extracted and transformed into a unique, compact hash code. The MATLAB implementation of this approach facilitates efficient computation and real-time performance evaluation. Experimental results demonstrate that the proposed method not only enhances the robustness against various image manipulations but also improves retrieval accuracy and computational efficiency when compared to existing image hashing techniques. This research contributes a more resilient and scalable solution to the field of digital image processing.