Reduction of JPEG2000 Compression Artifacts using Very Deep Super Resolution Approach for Multitemporal Multispectral Images

Nowadays, multispectral images are acquired by many different satellites. These satellites produce a large amount of data by traveling around the world. Efficient compression of these images are important issues. In order to solve this problem, the most used method is compression of the images with JPEG2000 method. However, distortion occurs after JPEG2000 compression, especially at low bit-rates. This situation affects the performance of some applications such as change detection, classification, anomaly detection etc. In this paper, in order to overcome compression artifacts, a very deep süper-resolution approach is proposed as post-processing after JPEG2000 decompression. In the experiments, scenes of the Onera dataset that is shared in the website of IEEE GRSS DASE are used. Experimental results show that the proposed method not only increases the image quality but also improves the change detection performance.