Treelet-based Bayer type CFA image denoising method

Abstract

The invention discloses a Treelet-based Bayer type CFA (Color Filter Array) image denoising method which mainly solves the problem that a large amount of residual noise occurs easily when the existing denoising method is directly applied to a CFA image. The method comprises the following steps: exacting high frequency information from an input noisy CFA image; performing blocking processing on the high frequency image, gradually exacting training data from all image blocks, and projecting training data to a Treelet basis matrix; obtaining denoised high frequency image blocks by contracting projection coefficients and performing inverse projection; and splicing all the denoised high frequency image blocks, and adding low frequency information input to the CFA image, so as to obtain a denoised CFA image. The method can directly perform adaptive denoising on the CFA image, simultaneously can reduce the residual noise in the denoised image in the condition that image detail is properly kept, and can be applied to the denoising processing on the CFA images captured through a single CCD (Charge Couple Device) or CMOS (Complementary Metal Oxide Semiconductor) sensor camera.

Description

technical field [0001] The invention belongs to the technical field of image processing, and further relates to a Bayer-type CFA image denoising method based on Treelet, which can be used for denoising processing of CFA images captured by a single CCD or CMOS sensor camera. Background technique [0002] Digital color images usually use red, green, and blue primary colors to represent color values, so three different two-dimensional matrices are required to represent them. For cost considerations, most cameras currently use a single CCD or CMOS sensor. By adding a color filter array CFA in front of the sensor, only one matrix is ​​used to represent the color image. There is only one color value at each pixel, and the other two color values ​​are interpolated according to its neighborhood information. This interpolation technique is called "demosaicing" technique. Due to the influence of electromagnetic effects and thermal effects on sensors, images captured by digital camera...

AI Technical Summary

Problems solved by technology

Although this method can be directly applied to Bayer-type CFA images without segmentation processing, the disadvantage is that there are still many noise residues after processing the PCA coefficients, especially in the case of high noise, the noise reduction effect is not good

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