public class UtilDenoiseWavelet extends Object
| Constructor and Description |
|---|
UtilDenoiseWavelet() |
| Modifier and Type | Method and Description |
|---|---|
static float |
estimateNoiseStdDev(ImageFloat32 subband,
float[] storage)
Robust median estimator of the noise standard deviation.
|
static float[] |
subbandAbsVal(ImageFloat32 subband,
float[] coef)
Computes the absolute value of each element in the subband image are places it into
'coef'
|
static double |
universalThreshold(ImageSingleBand image,
double noiseSigma)
Computes the universal threshold defined in [1], which is the threshold used by
VisuShrink.
|
public static float estimateNoiseStdDev(ImageFloat32 subband, float[] storage)
Robust median estimator of the noise standard deviation. Typically applied to the HH1 subband.
σ = Median(|Yij|)/0.6745
where σ is the estimated noise standard deviation, and Median(|Yij|)
is the median absolute value of all the pixels in the subband.
D. L. Donoho and I. M. Johnstone, "Ideal spatial adaption via wavelet shrinkage." Biometrika, vol 81, pp. 425-455, 1994
subband - The subband the image is being computed from. Not modified.storage - Used to temporarily store the absolute value of each element in the subband.public static float[] subbandAbsVal(ImageFloat32 subband, float[] coef)
public static double universalThreshold(ImageSingleBand image, double noiseSigma)
Computes the universal threshold defined in [1], which is the threshold used by VisuShrink. The same threshold is used by other algorithms.
threshold = σ sqrt( 2*log(max(w,h))
where (w,h) is the image's width and height.
[1] D. L. Donoho and I. M. Johnstone, "Ideal spatial adaption via wavelet shrinkage." Biometrika, vol 81, pp. 425-455, 1994
image - Input image. Only the width and height are used in computing this thresold.noiseSigma - Estimated noise sigma.Copyright © 2013. All Rights Reserved.