Explore MATLAB source code curated for "数字水印" with clean implementations, documentation, and examples.
Comprehensive techniques for digital watermark embedding, extraction, detection, and attacks including LSB (Least Significant Bit) and DCT (Discrete Cosine Transform) algorithms with code implementation insights
A digital watermark processing system primarily consists of two key processes: watermark embedding and watermark detection. (1) Watermark Embedding: Digital watermark (X), original image (I), and key/public key (K) are processed through a digital watermark embedding algorithm to generate the watermarked image (I*). This typically involves spatial domain techniques like LSB manipulation or frequency domain transformations such as DCT/DWT. (2) Watermark Detection: Digital watermark (X), watermarked image (I*), and key/public key (K) are processed through a detection algorithm to extract the watermark or verify its presence using correlation analysis or statistical methods. The program has been successfully tested and debugged.
Reference code for digital watermarking featuring checksum, LSB (Least Significant Bit), and patchwork embedding methods, including SNR calculation and watermark removal implementation with algorithm explanations
Digital watermark attack testing involves evaluating robustness through various methods including filtering, cropping, noise addition, JPEG compression, and other techniques. Implementation typically requires image processing algorithms and specific attack simulation functions.
MATLAB GUI implementation for digital watermarking using DWT and SVD algorithms with chaotic encryption. This graduation project code combines discrete wavelet transform (DWT) and singular value decomposition (SVD) for watermark embedding and extraction. Features chaotic encryption for enhanced security. After downloading, ensure proper image path configuration in the code.
Mini-programs for digital watermarking algorithms designed to assist beginners in understanding the fundamentals. Developed in MATLAB environment with practical code examples for embedding and extraction techniques.
A compact MATLAB-based digital watermarking algorithm demonstration designed to assist beginners in understanding fundamental concepts and implementation approaches in digital watermarking technology.
Blind watermark extraction does not require access to the original carrier image, making it highly applicable in information hiding and copyright protection. The proposed blind watermarking algorithm leverages block-based Discrete Cosine Transform (DCT) and Discrete Wavelet Transform (DWT), utilizing the characteristic where DCT and DWT coefficients exhibit consistent trends under attacks. Through adaptive selection of relational embedding and quantization embedding strategies, the robustness of blind watermark extraction is significantly enhanced. Additionally, dither modulation in quantization embedding facilitates flexible adjustment of watermark transparency and robustness. Extensive simulation results demonstrate strong resilience against noise interference, low-pass filtering, JPEG compression, and contrast enhancement attacks. Keywords: Digital Watermarking, Blind Watermarking, Relational Embedding.
Halftone image information hiding using computational holography, implemented in MATLAB for digital watermarking applications. This implementation demonstrates encoding and decoding processes for embedding identification data into images using holographic techniques.
A compact digital watermarking algorithm implementation designed to assist beginners in understanding fundamental concepts. Developed in MATLAB environment with practical code examples covering basic embedding and extraction techniques.