Methods and apparatus for determination of light sources of images and color vision matching of images

Abstract

The invention provides methods and apparatus for determination of light sources of images and color vision matching of images. The method for determination of light sources of images includes the steps of calculating the indicating value of each of a group of candidate light sources of an image, wherein each candidate light sources is described by corresponding coordinate pairs (p, q) in a chromacoordinate system; determining the threshold of the indicating values of the candidate light sources; identifying a subset of the candidate light sources with the indicating values not greater than the threshold value, and calculating the weight average of the corresponding coordinate pairs for all the candidate light sources in the subset to obtain the average coordinate pairs describing the light sources of the image in the chroma coordinate system.

Description

technical field [0001] The invention relates to the fields of color photography, digital camera, color printing and digital color image processing. Background technique [0002] All user color display devices are calibrated so that the displayed colors are at the standard "white point" chromaticity when red (R) = green (G) = blue (B) of the color channels, according to the International Commission on Illumination (International Commission on Illumination, referred to as CIE) standard, most of which are D65 or D50. Digital color cameras using complementary metal-oxide semiconductor (CMOS) or charge-coupled device (CCD) have different sensitivities to the RGB channels, resulting in a certain color cast in the original image ( For example, greenish). In addition, the color of objects will change due to the color of the light source (such as tungsten light or sunlight) and the reflection of surrounding objects on each other. Therefore, it is often necessary to adjust the "whi...

AI Technical Summary

Problems solved by technology

The traditional AWB algorithm is sensitive to the statistics of the scene content, and often encounters one or more of the following difficulties: 1) The color shift of the main color affects the result, 2) When there is no neutral color in the image, the probability of estimation error is high, 3) Incorrect camera calibration may result in scene statistics that differ from those used by the camera, 4) a large number of reference standards are required as training samples to establish reliable statistics, and, 5) the performance of the algorithm is limited by the number of components and The effect of component differences

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