Recover Water Bodies in Multi-spectral Satellite Images with Deep Neural Nets

On the days that surface is covered by thick clouds, the acquired images from optical satellites usually suffer missing information, caused to not able to use because we can't see anything under cloudy cover. Many methods have been proposed in order to recover the missing data, but those only recover the image from one or more images that seem to be referenced images, and those approaches mostly select the similar part or corresponding pixels to recover the original damaged. This research proposes a new approach for recovering damaged image, which aims to use this periodical weather pattern. The main idea is combining prediction and reconstruction techniques. For prediction, A time-series data of consecutive images will be used to predict the next image. This image will be used as referenced image for reconstruction process.