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NormalizeLocalContrast

Normalizes local contrast of the image using Wallis filter.

Name	Type	Range	Description
inMonoImage	Image		Monochromatic input image
inRoi	Region *		Range of pixels to be processed
inTargetMean	Real		Target local mean
inTargetVariance	Real	0.1 -	Target local variance
inUniformnessScale	Integer	1 - +	Radius of neighbourhood to uniformize
inBrightnessPreserveRatio	Real	0.0 - 1.0	How much of original brightness to be kept
outImage	Image		Output image

Only the following inMonoImage pixel formats are supported: 1xuint8, 1xint8, 1xuint16, 1xint16, 1xint32, 1xreal

Description

This filter resaturates every pixel of monochromatic image inMonoImage so that its neighbourhood matches approximately average of inTargetMean and variance of inTargetVariance using Wallis algorithm.

Parameter inUniformnessScale determines the radius of the neighbourhood.

Parameter inBrightnessPreserveRatio determines how much of the original brightness is kept on the resulting image.

New value of pixel is given by:

\[ P_{new} = A\ P_{old} + B \]

where

\[B = \frac{Var_{new} }{\frac{90}{CFC} + Var_{loc} } \] \[A = Mean_{loc}(1 - BPR) + Mean_{new}(BPR - B) \]

and

\(Dev_{loc}\) and \(Mean_{loc}\) are local deviation and mean respectively, taken from the square neighbourhood of radius inUniformnessScale
CFC is Contrast Force Constant, set to \(0.9\)
BPR is inBrightnessPreserveRatio

Examples

Example image

Output of NormalizeLocalContrast filter

Previous image with NormalizeImage filter applied to it

Remarks

After the filter is run on the image, the neighbourhoods of pixels do not have desired variance and average. First reason for that is presence of constants BPR and CFC. Second reason is that forcing matching given average would require solving system of as many linear equations as there are pixels on the image.

Errors

This filter can throw an exception to report error. Read how to deal with errors here: Error Handling

Error type	Description
DomainError	Image depth must be 1 in NormalizeLocalContrast filter

Complexity Level

This filter is available on Basic Complexity Level.