Cheng Xin, Liu Huashan
College of Information Science and Technology, Donghua University, Shanghai 201620, China.
Engineering Research Center of Digitized Textile and Apparel Technology, Ministry of Education, Shanghai 201620, China.
Sensors (Basel). 2020 Sep 25;20(19):5500. 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.
图像语义分割是计算机视觉中的关键问题之一。尽管在应用方面取得了巨大进展，但几乎所有的图像语义分割算法都因对细节缺乏敏感性、难以评估像素的全局相似性或两者兼而有之，而未能取得令人满意的分割结果。后处理增强方法作为改善算法上述固有缺陷的极其关键的手段，几乎都基于条件随机场（CRF）。受CRF启发，本文从滤波角度提出了一种理论简单的新型后处理增强框架，并设计了一种新的加权复合滤波器（WCF），以在统一框架中增强分割掩码。首先，通过调整权重比，将WCF分解为局部部分和全局部分。其次，设计了一种引导图像滤波器作为局部滤波器，它可以恢复边界信息以呈现必要的细节。此外，设计了一种基于最小生成树（MST）的滤波器作为全局滤波器，为图像匹配提供全局像素相似性的自然度量。第三，设计了一个统一的后处理增强框架，包括选择和归一化、WCF和argmax。最后，通过实验验证了所提增强方法的有效性和优越性及其应用范围。
