Edge adaptive deblocking method in the satellite image for real-time application

Blocking artifacts is commonly occurred in compressed images due to the properties of lossy compression techniques. In this paper, we present a deblocking algorithm for the satellite images generated by KOrean Multi-Purpose SATellite (KOMPSAT)-2. The KOMPSAT-2 images are compressed with the equal quantization step size for the rows in a given image according to region complexity. However, this approach has a problem that relatively less complicated regions within the same row cause more blocking artifacts. Removing these artifacts with a general deblocking algorithm can blur undesired and complex regions. Additionally, the general filter lacks in preserving the curved edges. Therefore, we present an adaptive filtering scheme for removing blocking artifacts while preserving the image details. It uses prior information given by quantization step size and content analysis. Particularly, directional low pass filter using principle components analysis (DLFPCA) is introduced to reduce staircase noise around the edges. Experimental results showed that the proposed method outperformed the existing approaches in terms of an objective quality metric and processing time.