Study on Vignetting Correction of Uav Images and Its Application to 2010 Ms7.0 Lushan Earthquake, China

As the UAV is widely used in earthquake disaster prevention and mitigation, the efficiency of UAV image processing determines the effectiveness of its application to pre-earthquake disaster prevention, post-earthquake emergency rescue, and disaster assessment. Because of bad weather conditions after destructive earthquake, the wide field cameras captured images with serious vignetting phenomenon, which can significantly affects the speed and efficiency of image mosaic, especially the extraction of pre-earthquake building and geological structure information and also the accuracy of post-earthquake quantitative damage extraction. In this paper, an improved radial gradient correction method (IRGCM) was developed to reduce the influence from random distribution of land surface objects on the images based on radial gradient correction method (RGCM, Y. Zheng, 2008; 2013). First, a mean-value image was obtained by the average of serial UAV images. It was used as calibration instead of single images to obtain the comprehensive vignetting function by using RGCM. Then each UAV image would be corrected by the comprehensive vignetting function. A case study was done to correct the UAV images sequence, which were obtained in Lushan County after Ms7.0 Lushan, Sichuan, China earthquake occurred on April 20, 2013. The results show that the comprehensive vignetting function generated by IRGCM is more robust and accurate to express the specific optical response of camera in a particular setting. Thus it is particularly useful for correction of a mass UAV images with non-uniform illuminations. Also, the correction process was simplified and it is faster than conventional methods. After correction, the images have better radial homogeneity and clearer details, to a certain extent, which reduces the difficulties of image mosaic, and provides a better result for further analysis and damage information extraction. Further test shows also that better results were obtained by taking advantage of comprehensive vignetting function to the other UAV image sequences from different regions. The research was supported by these projects, NO.2012BAK15B02 and 2013IES010106.