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The experimental results show that, compared with EnlightGAN, Zero-DCE, Retinex, and SSE, the algorithm in this paper (DCE-Denoise-Net) has good results on image quality metrics such as information entropy, Brisque, NIQE, and PIQE in the absence of reference images. The image quality is improved. On the basis of improving the low visibility of low-light images, denoising was achieved. It is more suitable for low-light pig face image enhancement in a real breeding environment.<\/jats:p>","DOI":"10.3233\/jcm-226858","type":"journal-article","created":{"date-parts":[[2023,6,13]],"date-time":"2023-06-13T10:26:11Z","timestamp":1686651971000},"page":"2699-2709","source":"Crossref","is-referenced-by-count":1,"title":["Improved Zero-DCE for pig face image enhancement with low-light and high-noise"],"prefix":"10.66113","volume":"23","author":[{"given":"Ronghua","family":"Gao","sequence":"first","affiliation":[{"name":"Information Technology Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing, China"},{"name":"National Engineering Research Center of Agricultural Informatization, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiabin","family":"Dong","sequence":"additional","affiliation":[{"name":"Institute of mathematical, China University of Geosciences, Beijing, China"},{"name":"National Engineering Research Center of Agricultural Informatization, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qifeng","family":"Li","sequence":"additional","affiliation":[{"name":"Information Technology Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing, China"},{"name":"National Engineering Research Center of Agricultural Informatization, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lu","family":"Fenga,c","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"55691","reference":[{"issue":"2","key":"10.3233\/JCM-226858_ref1","first-page":"391","article-title":"Individual Identification of Pigs based on Multi-scale Convolutional Network in a Variable Environment","volume":"42","author":"Wang","year":"2020","journal-title":"Acta Agriculturae Universitis Jiangxiensis."},{"issue":"4","key":"10.3233\/JCM-226858_ref2","first-page":"179","article-title":"Instance-level Segmentation Method for Group Pig Images Based on Deep Learning","volume":"50","author":"Gao","year":"2019","journal-title":"Transactions of the Chinese Society for Agricultural Machinery."},{"key":"10.3233\/JCM-226858_ref3","doi-asserted-by":"crossref","unstructured":"Pizer SM, Amburn EP, Austin JD, et al., Adaptive histogram equalization and its varia-tions. 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