A Novel Post-Processing Method Based on a Weighted Composite Filter for Enhancing Semantic Segmentation Results

• Published in: Sensors (Basel, Switzerland) Vol. 20; no. 19; p. 5500
• Main Authors: Cheng, Xin, Liu, Huashan
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 25.09.2020; MDPI
• Subjects: Algorithms; Computer vision; Conditional random fields; Graph theory; guided image filter; Image enhancement; Image filters; image semantic segmentation; Letter; Methods; minimum spanning tree (MST)-based filter; Neural networks; Pixels; post-processing enhancement; Post-production processing; Semantic segmentation; Semantics; Similarity; weighted composite filter (WCF)
• ISSN: 1424-8220; 1424-8220
• DOI: 10.3390/s20195500

Image semantic segmentation is one of the key problems in computer vision. Despite the enormous advances in applications, almost all the image semantic segmentation algorithms fail to achieve satisfactory segmentation results due to lack of sensitivity to details, or difficulty in evaluating the global similarity of pixels, or both. Posting-processing enhancement methods, as the outstandingly crucial means to ameliorate the above-mentioned inherent flaws of algorithms, are almost based on conditional random fields (CRFs). Inspired by CRFs, this paper proposes a novel post-processing enhancement framework with theoretical simplicity from the perspective of filtering, and a new weighted composite filter (WCF) is designed to enhance the segmentation masks in a unified framework. First, by adjusting the weight ratio, the WCF is decomposed into a local part and a global part. Secondly, a guided image filter is designed as the local filter, which can restore boundary information to present necessary details. Moreover, a minimum spanning tree (MST)-based filter is designed as the global filter to provide a natural measure of global pixel similarity for image matching. Thirdly, a unified post-processing enhancement framework, including selection and normalization, WCF and argmax, is designed. Finally, the effectiveness and superiority of the proposed method for enhancement, as well as its range of applications, are verified through experiments.