Method for checking digital camera color reduction

Abstract

A detection method of color restoration of digital cameras includes the following steps: firstly, a standard color card is put on a back wall in a lamphouse, and the LAB value of each color block on the standard color card is detected by a luminance and chroma meter and taken as a standard LAB value of the color block to be memorized into a computer; secondly, under the same measurement condition, the optical axis of the camera is vertical to the surface of the color block in the lamphouse and then a picture is taken; thirdly, the taken picture is input into the computer, the RGB value of each color block of the picture is obtained and converted into the LAB value, and the total color difference of each color block is calculated. The detection method of color restoration of digital cameras can correctly and reliably detect the color deviation of images and accurately calculate the color deviation degree of images. The calculating effect of the method on the color deviation is in line with the feeling of human eyes, and the calculation has high efficiency and is objective and accurate.

Description

technical field [0001] The invention relates to digital camera image quality color restoration evaluation and automatic detection. Background technique [0002] The quality evaluation of digital images is usually measured from several aspects such as sharpness, white balance, color reproduction, gray scale, and the number of dead pixels, and the detection and quantification of the degree of color restoration and sharpness are the difficulties. [0003] Currently, there are two commonly used and most authoritative digital image quality detection methods: subjective evaluation detection method and objective evaluation detection method. The subjective evaluation method is to let the observer judge the quality of the test image according to the visual effect according to some pre-specified evaluation scales or their own experience, and give a quality score, and perform weighted average on the scores given by all observers. It is the subjective quality evaluation of the image. ...

AI Technical Summary

Problems solved by technology

[0012] These algorithms have certain limitations. They cannot detect the color cast of the image correctly and reliably in any situation, let alone estimate the degree of color cast of the image accurately, such as when the environment is too bright or too dark, or the background of the image When it is the sea or the blue sky, the grayscale world method is almost completely ineffective; and when there is no white in the photographed object, the detection result of the white area method is also unreal; the neural network method and the prior knowledge rule need to be accumulated through learning. Or prior knowledge to judge, with greater limitations

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