Color interpolation method based on adaptive guided filtering

Abstract

The invention discloses a color interpolation method based on adaptive guided filtering. The method includes the steps of image input, wherein an image to be processed is input; filtering, wherein the discretization scheme of an adopted adaptive guided filter is determined according to the type of the input image to carry out directional adaptive guided filtering; G channel color component interpolation, wherein the GX value is calculated with known neighbor pixel values according to adaptive weight values determined in 8 directions; B and R channel color component interpolation, wherein interpolation is carried out on unknown pixels of a B channel after all pixel values of a G channel are acquired, the possible interpolation direction of position pixels is estimated with the color difference of G and B, and the color remainders rBG of unknown pixels BX of the B channel in four directions are calculated; correction, wherein G, R and B color components are finely corrected; interpolation result output, wherein a color interpolation result is output.

Description

technical field [0001] The invention relates to the field of image processing, in particular to a color interpolation method based on adaptive guided filtering. Background technique [0002] As digital media information such as images and videos become more and more important communication methods, in various imaging devices such as smartphones and cameras, the CCD and CMOS imaging devices used are the most important components, which directly affect the captured images. the quality of. Considering the limitation of cost and volume, most cameras use CCD or CMOS of a single color channel as the device for receiving images. In order to completely describe a color pixel, at least three color components of red (Red, R), green (Green, G) and blue (Blue, B) are required. It is therefore common to overlay a color filter array on the image sensor. Since the Bayer format array has good color sensitivity and restoration properties, it is widely used in various image sensors. Each ...

AI Technical Summary

Problems solved by technology

[0003] However, in the interpolation method of the prior art, the direction prediction is inaccurate, and it cannot adapt to different image contents, resulting in problems such as low fitting accuracy of the relationship between adjacent pixels.

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