Modification of fastNlMeansDenoisingMulti function for colored images sequences

dst = cv.fastNlMeansDenoisingColoredMulti(srcImgs, imgToDenoiseIndex, temporalWindowSize)
dst = cv.fastNlMeansDenoisingColoredMulti(..., 'OptionName',optionValue, ...)

Input

• srcImgs Input 8-bit 3-channel images sequence. All images should have the same type and size.
• imgToDenoiseIndex Target image to denoise index in srcImgs sequence (0-based index).
• temporalWindowSize Number of surrounding images to use for target image denoising. Should be odd. Images from imgToDenoiseIndex - temporalWindowSize/2 to imgToDenoiseIndex + temporalWindowSize/2 from srcImgs will be used to denoise srcImgs{imgToDenoiseIndex} image.

Output

• dst Output image with the same size and type as srcImgs images.

Options

• H Parameter regulating filter strength for luminance component. Bigger H value perfectly removes noise but also removes image details, smaller H value preserves details but also preserves some noise. default 3
• HColor The same as H but for color components. default 3
• TemplateWindowSize Size in pixels of the template patch that is used to compute weights. Should be odd. Recommended value 7 pixels. default 7
• SearchWindowSize Size in pixels of the window that is used to compute weighted average for given pixel. Should be odd. Affect performance linearly: greater SearchWindowsSize - greater denoising time. Recommended value 21 pixels. default 21
• FlipChannels whether to flip the order of color channels in input srcImgs{i} and output dst, between MATLAB's RGB/RGBA order and OpenCV's BGR/BGRA (input: RGB/RGBA->BGR/BGRA, output: BGR/BGRA->RGB/RGBA). default false

The function converts images to CIELAB colorspace and then separately denoise L and AB components with given H parameters using cv.fastNlMeansDenoisingMulti function.