Explore MATLAB source code curated for "剪切" with clean implementations, documentation, and examples.
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.
An algorithm for information hiding implemented in MATLAB, including a suite of image processing functions for various attacks and transformations: mycompress.m for JPEG lossy compression, mycrop.m for image cropping, myhighpass.m for high-pass filtering, mylowpass.m for low-pass filtering, mynoise.m for Gaussian and salt-and-pepper noise addition, myresize.m for image scaling, myrotate.m for image rotation, mywiener.m for Wiener filtering, and myattack.m as a comprehensive collection of all the above attacks.
Robust DCT-domain watermarking that withstands compression, cropping, and other common attacks
This MATLAB code simulates the effects of clipping and filtering on Peak-to-Average Power Ratio (PAPR) reduction in OFDM-based wireless standards. The implementation includes performance evaluation of Bit Error Rate (BER) versus Signal-to-Noise Ratio (SNR) for original OFDM signals with PAPR reduction using clipping and filtering schemes over Additive White Gaussian Noise (AWGN) channel. The code demonstrates key signal processing operations including signal clipping threshold implementation, frequency-domain filtering techniques, and iterative PAPR reduction algorithms.
1. Master the algorithm principles of geometric transformations including image translation, shearing, scaling, rotation, and mirroring 2. Acquire proficiency in fundamental image geometric transformation functions within the MATLAB programming environment