Automatic white balance correcting method

Abstract

The invention discloses an automatic white balance correcting method which comprises the following steps of 1, respectively acquiring histogram information of each RGB channel of a current image; 2, selecting an appropriate algorithm mode through the characteristic of the image RGB channel histogram, wherein the algorithm mode comprises a histogram matching algorithm and a histogram translation algorithm; 3, performing histogram adjustment, wherein calculation of a new pixel value of the RGB channel is required in a histogram matching mode, and calculation of a translation coefficient is required in a histogram translation mode; and 4, converting each pixel value of the RGB channel, thereby obtaining a corrected image. According to the automatic white balance correcting method, effectiveness determining is performed on the white balance algorithm based on histogram matching through using the distribution characteristic of the RGB channel histogram; according to the characteristics in histogram matching and histogram translation, defects of the existing histogram-based white balance algorithm are compensated; a high correction effect is insured; and furthermore an application rangeof the algorithm is greatly expanded.

Description

Technical field [0001] The invention relates to the technical field of digital image processing, in particular to an automatic white balance correction method with excellent correction effect and wide application range. Background technique [0002] Image sensors imitate human vision imaging, but sensors do not have some characteristics of human vision, and color constancy is one of them. Color constancy means that the human visual system is not affected by the light source information within a certain range, and the imaging of the image sensor does not have this characteristic. The image will have the color cast information of the light source color under which color light source is imaged. Pictures taken at low color temperatures are obviously reddish, and pictures taken at high color temperatures are noticeably blue. But the color cast information is not what humans need. On the contrary, the light source information causes the color deviation of the things reflected in the p...

AI Technical Summary

Problems solved by technology

The assumption-based white balance algorithm relies on certain assumptions, such as the gray world method and the perfect reflection method. The algorithm is simple, but the algorithm fails when the assumption is not true; the automatic white balance algorithm based on prior knowledge relies on a large number of sample data to obtain parameter values. , such as color gamut mapping algorithm, color correlation algorithm, neural network algorithm, the algorithm has high correction accuracy and wide application range, but the algorithm is complex; the histogram-based automatic white balance algorithm corrects the color cast by adjusting the histogram of the image, for example, based on Automatic white balance algorithm of histogram stretching and histogram matching, this kind of algorithm does not rely on assumptions, the algorithm is simple, the correction effect is good, but the scope of application is narrow

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