Package boofcv.alg.denoise.wavelet

Class DenoiseBayesShrink_F32

java.lang.Object

boofcv.alg.denoise.wavelet.SubbandShrink<GrayF32>

boofcv.alg.denoise.wavelet.DenoiseBayesShrink_F32

All Implemented Interfaces:

DenoiseWavelet<GrayF32>

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/σ_X
where σ is the noise standard deviation and σ_X 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

Field Summary

Fields inherited from class boofcv.alg.denoise.wavelet.SubbandShrink

rule

Constructor Summary

Constructors

Constructor	Description
DenoiseBayesShrink_F32(ShrinkThresholdRule<GrayF32> rule)

Method Summary

Modifier and Type	Method	Description
protected 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.

Methods inherited from class boofcv.alg.denoise.wavelet.SubbandShrink

performShrinkage

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Details

DenoiseBayesShrink_F32

public DenoiseBayesShrink_F32(ShrinkThresholdRule<GrayF32> rule)

Method Details

computeThreshold

protected Number computeThreshold(GrayF32 subband)

Description copied from class: SubbandShrink

Compute the threshold for the specified subband.

Specified by:

computeThreshold in class SubbandShrink<GrayF32>

Parameters:

subband - Subband whose threshold is being computed.

denoise

public void denoise(GrayF32 transform,
 int numLevels)

Description copied from interface: DenoiseWavelet

Removes noise from the multi-level wavelet transform.

Parameters:

transform - Transform of the original image.

numLevels - NUmber of levels in the transform.