Method for eliminating dead pixels in RAW-RGB image

Abstract

The invention provides a method for eliminating dead pixels in an RAW-RGB image, which comprises the steps of converting R-pixels and B-pixels in an RAW-RGB image into G-pixels so as to convert the RAW-RGB image into a G-domain image, performing dead pixel judgment in the G-domain image, and then carrying out dead pixel elimination and restoration in the G-domain image. In the above process, the method can be implemented by only utilizing data of the current line where a dead pixel is located and a previous line, so that the volume of data required in the current technical scheme is greatly reduced, the time of data processing is reduced, and the possibility of real-time processing is increased. Meanwhile, the required hardware area is reduced, and the consumption of resources is lowered.

Description

technical field [0001] The invention relates to the field of image processing, in particular to a method for eliminating dead pixels in RAW-RGB images. Background technique [0002] The image sensor contains a color filter array (color filter array), that is, a Bayer filter, so that the light collected at each point on the sensor can only collect light of one wavelength after being filtered by the Bayer filter, and the light collected at each point on the sensor passes through The light of the corresponding color passing through the filtering process is red, blue or green. The photosensitive array in the image sensor converts the collected light signal into an electrical signal; the image sensor then converts the electrical signal into a digital signal, and the converted digital signal is the pixel value corresponding to each point of light collected on the current sensor. The image sensor composes a corresponding original image through the pixels corresponding to the array...

AI Technical Summary

Problems solved by technology

Some existing bad pixel detection algorithms either have a relatively high false detection rate of bad pixels in the image, or the processing effect of bad pixels is not good, or the time required for image processing is long, the real-time performance is not enough, or the required hardware area is large and resource Consumption is relatively large

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