Color Temperature Estimation of Scene Illumination by the Sensor Correlation Method

摘要

In many fields, including computer vision and image understanding, it is important to obtain knowledge about the illuminating light source from color images. This paper presents an algorithm which improves the sensor correlation method used to classify the source illuminating an imaged scene, and also presents an application. First, we wish to derive a perceptually uniform illumination classification as an alternative to the conventional physical light source classification based on the color temperature scale. For this purpose, the inverse (reciprocal) color temperature scale called mired is used. Second, we calculate the correlation, not between the pixels and the source color region (illuminant gamut), but between the image gamut and the illuminant gamut. Third, a scaling operation for the image is introduced so that the illuminant gamut can be determined by adjusting the intensity difference between images. The validity of the proposed algorithm is evaluated in detail by using an actual image database. Then the proposed source classification method is applied to color compensation. When the color temperature of the source is estimated, the image obtained when the same scene is illuminated by a different source can be predicted. It is shown that color compensation based on the relation between the sensor output and the color temperature is useful in such an application.