Vignetting Correction Through Color-Intensity Map Entropy Optimization

Vignetting correction is an essential process of image signal processing. It is an important part for obtaining high-quality images, but the research in this field has not been fully emphasized. The mainstream methods are based on calibration which processes are complex. And many methods get low accuracy and poor robustness in practical. In this paper, we analyzed the optical principle of vignetting and its influence on the image. Then, we proposed an algorithm based on color-intensity map entropy optimization to correct image vignetting. Moreover, because of the lack of dataset of vignetting, we proposed a method for constructing vignetting image dataset through capturing the real scenes. Compared with the dataset generated through simulation, our dataset is more authentic and reliable. Many experiments have been carried out on this dataset, and the results proved that the proposed algorithm achieved the best performance.