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Novel Post-Processing Method Based on a Weighted Composite Filter for Enhancing Semantic Segmentation Results
Sensors ( IF 3.4 ) Pub Date : 2020-09-25 , DOI: 10.3390/s20195500
Xin Cheng , Huashan Liu

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.

中文翻译:

基于加权复合滤波器的后处理增强语义分割结果的新方法

图像语义分割是计算机视觉中的关键问题之一。尽管应用取得了巨大的进步,但是由于缺乏对细节的敏感度或难以评估像素的全局相似性,或者几乎同时存在这两种情况,几乎所有的图像语义分割算法都无法获得令人满意的分割结果。作为改善上述算法固有缺陷的至关重要的手段,后期处理增强方法几乎都是基于条件随机字段(CRF)。受CRF的启发,本文从滤波的角度出发,提出了一种具有理论简单性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)来在统一框架中增强分割蒙版。首先,通过调整重量比,WCF分解为本地部分和全局部分。其次,将导引图像滤波器设计为局部滤波器,可以恢复边界信息以呈现必要的细节。此外,基于最小生成树(MST)的滤波器被设计为全局滤波器,以提供用于图像匹配的全局像素相似度的自然度量。第三,设计了一个统一的后处理增强框架,包括选择和规范化,WCF和argmax。最后,通过实验验证了所提出的增强方法的有效性和优越性,以及其应用范围。基于最小生成树(MST)的滤波器被设计为全局滤波器,以提供用于图像匹配的全局像素相似度的自然度量。第三,设计了一个统一的后处理增强框架,包括选择和规范化,WCF和argmax。最后,通过实验验证了所提出的增强方法的有效性和优越性,以及其应用范围。基于最小生成树(MST)的滤波器被设计为全局滤波器,以提供用于图像匹配的全局像素相似度的自然度量。第三,设计了一个统一的后处理增强框架,包括选择和规范化,WCF和argmax。最后,通过实验验证了所提出的增强方法的有效性和优越性,以及其应用范围。
更新日期:2020-09-25
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