public class DenoiseBayesShrink_F32 extends SubbandShrink<GrayF32>
Denoises images using an adaptive soft-threshold in each sub-band computed using Bayesian statistics.
Wavelet coefficients are modified using a standard soft-thresholding technique. The threshold
is computing using an adaptively for each sub-band, as follows:
T = σ2/σX
where σ is the noise standard deviation and σX is the signal standard deviation.
S. Change, B. Yu, M. Vetterli, "Adaptive Wavelet Thresholding for Image Denoising and Compression" IEEE Tran. Image Processing, Vol 9, No. 9, Sept. 2000
rule| Constructor and Description |
|---|
DenoiseBayesShrink_F32(ShrinkThresholdRule<GrayF32> rule) |
| Modifier and Type | Method and Description |
|---|---|
protected java.lang.Number |
computeThreshold(GrayF32 subband)
Compute the threshold for the specified subband.
|
void |
denoise(GrayF32 transform,
int numLevels)
Removes noise from the multi-level wavelet transform.
|
performShrinkagepublic DenoiseBayesShrink_F32(ShrinkThresholdRule<GrayF32> rule)
protected java.lang.Number computeThreshold(GrayF32 subband)
SubbandShrinkcomputeThreshold in class SubbandShrink<GrayF32>subband - Subband whose threshold is being computed.public void denoise(GrayF32 transform, int numLevels)
DenoiseWavelettransform - Transform of the original image.numLevels - NUmber of levels in the transform.