Explore MATLAB source code curated for "离散余弦变换" with clean implementations, documentation, and examples.
Digital watermarking system based on Discrete Cosine Transform (DCT), including watermark embedding and extraction processes, with considerations for common watermarking attacks and robustness enhancement techniques
This project demonstrates data dimensionality reduction using Discrete Cosine Transform combined with Principal Component Analysis, applicable to pattern recognition tasks like face recognition, palmprint analysis, expression classification, and fingerprint identification. The implementation involves signal transformation followed by feature extraction techniques.
MATLAB Image Orthogonal Transformations - Universal Orthogonal Transform Operators including Fourier Transform, Discrete Cosine Transform, Walsh-Hadamard Transform, Radon Transform, and Wavelet Transform with implementation approaches
An audio watermarking implementation utilizing Discrete Cosine Transform (DCT), synchronization signals, and segmented audio processing for robust watermark embedding and extraction.
MATLAB implementation of 2D Fourier Transform, Discrete Cosine Transform, and Wavelet Transform with comprehensive code examples and algorithm explanations.
Implementation of digital watermarking using Discrete Cosine Transform (DCT) - seeking suggestions for code optimization and algorithm improvements
(1) Visualization of Discrete Cosine Transform (DCT) basis functions as grayscale images (2) Visualization of Discrete Fourier Transform (DFT) basis functions as grayscale images
Implementation of Discrete Cosine Transform (DCT) for grayscale and color images, with appropriate DCT coefficient threshold selection for inverse DCT transformation.
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.
The compressed archive contains source code implementations for image compression using Wavelet Transform, Fourier Transform, Hadamard Transform, and Discrete Cosine Transform, along with a program for plotting image histograms and histograms of histogram-equalized images. The implementations include key algorithms for frequency-domain analysis and image compression techniques.