MATLAB Source Code for Digital Image Watermarking: Attacks, Embedding, and Extraction

This repository provides MATLAB source code for digital image watermarking attacks, embedding, and extraction procedures. Digital image watermarking is a technology designed to protect the copyright and integrity of digital images by embedding hidden information such as copyright details, owner information, or authentication data. To evaluate the security and robustness of digital image watermarking systems, three fundamental components must be implemented: attack simulation, watermark embedding, and watermark extraction. Watermark attacks refer to attempts to disrupt or remove digital watermarks from images. Attackers may employ various techniques and algorithms to detect, modify, or eliminate embedded watermark information. Researching attack methods helps improve watermark algorithm security and robustness. In MATLAB implementations, common attacks include noise addition (using imnoise function), filtering operations (medfilt2 for median filtering), geometric transformations (imrotate, imresize), and compression attacks (imwrite with quality parameters). Watermark embedding is the process of inserting watermark information into host images. Embedding algorithms typically leverage image characteristics and watermark requirements, employing specific embedding rules to insert data into particular image regions or frequency domains. Common MATLAB techniques include Discrete Wavelet Transform (DWT) based embedding using wavedec2/waverec2 functions, Least Significant Bit (LSB) substitution through bit manipulation, and Discrete Cosine Transform (DCT) based methods with dct2/idct2. These approaches balance visibility constraints with robustness requirements. Watermark extraction involves recovering embedded information from watermarked images. Extraction algorithms reverse the embedding process according to specific rules to retrieve watermark data. MATLAB implementations typically involve correlation detection, inverse transformation operations, or threshold-based extraction methods. Proper extraction validation ensures watermark correctness and integrity through similarity metrics like Peak Signal-to-Noise Ratio (PSNR) or Structural Similarity Index (SSIM). Using MATLAB source code for experimenting with digital image watermarking provides significant advantages due to MATLAB's comprehensive image processing toolbox and algorithm libraries. Researchers can efficiently implement, test, and compare various watermarking techniques through functions like image reading (imread), transformation tools, and statistical analysis capabilities. This technical documentation aims to facilitate deeper understanding of digital watermarking processes. For additional questions or implementation details, please feel free to request further clarification.