Explore MATLAB source code curated for "高频系数" with clean implementations, documentation, and examples.
Small image denoising program featuring wavelet-based thresholding. Key algorithm steps include: th=sigma*sqrt(2*log10(L*T)) for threshold calculation, ch=c(1,num(4-i,1):num(4-i,3)+step(4-i)-1) for high-frequency coefficient extraction, and implementing threshold processing through ch(j)=sign(ch(j))*(abs(ch(j))-2*th/(1+exp(m*(ch(j)^2)))) using a custom soft-thresholding function with sigmoid modulation.
This paper proposes an infrared and visible light image fusion method utilizing the Non-Subsampled Contourlet Transform (NSCT). The approach implements weighted fusion for high-frequency coefficients by combining activity measures and multi-resolution coefficient correlations, while low-frequency coefficients are processed through local gradient-based activity measurement with a hybrid weighted-selection fusion rule.
(1) Signal wavelet decomposition for frequency analysis, (2) Threshold quantization of high-frequency coefficients from wavelet decomposition for noise reduction, (3) Signal reconstruction using decomposed wavelet coefficients and quantized high-frequency coefficients
Generate a signal and perform wavelet decomposition to obtain approximation (low-frequency) and detail (high-frequency) coefficients, with implementation insights using Python's PyWavelets library.