Intra Coding With Geometric Information for Urban Building Scenes

Abstract

Regarding the interior non-local correlations of image content, the intra predictions in image/video coding standards have still not exploited them efficiently. In this article, we propose an intra coding method that leverages the geometric information extracted from the image content to strengthen the coding performance. During the process of image capturing, if the imaging plane of the camera is not fronto-parallel to the surface of an object in reality, the repetitive patterns on the object's surface in real world will appear with a scale shift in the image domain. Thus, the corresponding potential non-local redundancy cannot be removed through the direct utilization of intra block copy and its variants. To address this problem, we begin with a theoretic analysis into the perspective transformation matrix and derive the underlying geometric information that causes the scale shift in the image domain; afterwards, we propose an intra coding framework based on the geometric information to alleviate the scale shift. It is essential for the coding framework to realize block matching in the rectified domain. Our framework mainly consists of two components, i.e., the intra block copy in the rectified domain through planar perspective transformation to obtain a more accurate prediction for the current coding block and the non-local post-processing filtering in the rectified domain after decompression to achieve a better quality of the reconstructed image. The experimental results show that our proposed method can achieve as high as 18% and an average of 5.0% bit-rate saving on the common dataset Urban100 compared to the HEVC reference software HM-SCC-extension with intra block copy and non-local post-processing filtering.