Performance Impact of $JP2$ Compression on Semantic Segmentation of PolSAR Images

Future PolSAR missions are expected to collect vast quantities of data, which can significantly add to the storage cost of various geospatial cloud driven applications. Data compression techniques like those prescribed by the JPEG2000 (JP2) standard might help counteract this cost. However, it is important to measure the impact on target application performance due to these techniques. In this paper, the impact of JP2 and JPEG compression on classification performance of PolSAR data is studied and it has been found that compression has no significant impact on Deep Neural Network (DNN) classification performance.