Reconstruction of Cloud Contaminated Remote Sensing Images Using Inpainting Strategy

This paper focuses a method for cloud detection and their reconstruction technique. Detecting these portions of an image and then filling in the missing data is an important photo editing work. The filling-in approach such as inpainting techniques, which aim at filling holes in remote sensing images by propagating surrounding structures and texture information. Inpainting technique is a novel method for completing missing parts caused by the detection of foreground or background elements from an image.Reconstruction of missing data in remotely sensed image is of great challenge due to its complexity. These images may be partly contaminated by cloud. Detection of these clouds and accurate reconstruction of cloud removed area in satellite image is done here. To improve the accuracy in remotely sensed images, efficient inpainting techniques can be applied for reconstruction of missing regions. Large areas with lots of information lost are harder to reconstruct, because information in other parts of the image is not enough to get an impression of what is missing. Image inpainting is not to recover the original image, but to create some image that has a close resemblance with the original image. In this paper two different methods are proposed for filling in process. The first method involves reconstruction process by Exemplar Inpainting whereas the other method uses the Modified Exemplar inpainting. The entire process is developed using MATLAB software. The proposed method of cloud detection here is simple and easily applied to all cloud cover images.