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However, the existing energy models are mainly deterministic, which cannot adapt to processing low-quality images, especially when there exists a large proportion of vague areas. In order to perform better in processing these low-quality images, in this paper, we construct the smoothing term based on a fuzzy model, which includes fuzzy segmentation, the fuzzy network between the superpixels and the fuzzy relationship between the pixels. These can be compatible with the uncertainty in the image. In addition, to explain the rationality of the calculation of the degree of correlation between superpixels and further elaborate on the property of these degrees between each superpixel, we propose five corresponding theorems with proofs. After we solve the energy model combined with our proposed smoothing term, we compare our disparity results with the corresponding deterministic model and several state-of-the-art algorithms in the experiment. The results verify the effectiveness of the proposed algorithm.<\/jats:p>","DOI":"10.1093\/comjnl\/bxad015","type":"journal-article","created":{"date-parts":[[2023,3,13]],"date-time":"2023-03-13T15:47:59Z","timestamp":1678722479000},"page":"746-761","source":"Crossref","is-referenced-by-count":1,"title":["A New Fuzzy Smoothing Term Model For Stereo Matching"],"prefix":"10.1093","volume":"67","author":[{"given":"Zhang","family":"Hongjin","sequence":"first","affiliation":[{"name":"Laboratory of Algorithms for Cognitive Models, Shanghai Key Laboratory of Data Science, School of Computer Science, Fudan University , Shanghai 200433 China"}]},{"given":"Wei","family":"Hui","sequence":"additional","affiliation":[{"name":"Laboratory of Algorithms for Cognitive Models, Shanghai Key Laboratory of Data Science, School of Computer Science, Fudan University , Shanghai 200433 China"}]},{"given":"Wang","family":"Bo","sequence":"additional","affiliation":[{"name":"Laboratory of Algorithms for Cognitive Models, Shanghai Key Laboratory of Data Science, School of Computer Science, Fudan University , Shanghai 200433 China"}]}],"member":"286","published-online":{"date-parts":[[2023,3,10]]},"reference":[{"key":"2024021913320408200_ref1","doi-asserted-by":"crossref","DOI":"10.1109\/CVPRW.2019.00079","article-title":"Real-time dense stereo embedded in a uav for road inspection","volume-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition Workshops","author":"Fan","year":"2019"},{"key":"2024021913320408200_ref2","doi-asserted-by":"crossref","first-page":"173","DOI":"10.1016\/j.image.2015.09.012","article-title":"Robust non-local stereo matching for outdoor driving images using segment-simple-tree","volume":"39","author":"Pham","year":"2015","journal-title":"Signal Process. 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