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However, bottom-up saliency detection models are limited in their ability to explore light field features. In this paper, we propose a light field saliency detection method that focuses on depth-induced saliency, which can more deeply explore the interactions between different cues. First, we localize a rough saliency region based on the compactness of color and depth. Then, the relationships among depth, focus, and salient objects are carefully investigated, and the focus cue of the focal stack is used to highlight the foreground objects. Meanwhile, the depth cue is utilized to refine the coarse salient objects. Furthermore, considering the consistency of color smoothing and depth space, an optimization model referred to as color and depth-induced cellular automata is improved to increase the accuracy of saliency maps. Finally, to avoid interference of redundant information, the mean absolute error is chosen as the indicator of the filter to obtain the best results. The experimental results on three public light field datasets show that the proposed method performs favorably against the state-of-the-art conventional light field saliency detection approaches and even light field saliency detection approaches based on deep learning.<\/jats:p>","DOI":"10.3390\/e25091336","type":"journal-article","created":{"date-parts":[[2023,9,15]],"date-time":"2023-09-15T02:54:13Z","timestamp":1694746453000},"page":"1336","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Exploring Focus and Depth-Induced Saliency Detection for Light Field"],"prefix":"10.3390","volume":"25","author":[{"ORCID":"https:\/\/orcid.org\/0009-0002-8859-2209","authenticated-orcid":false,"given":"Yani","family":"Zhang","sequence":"first","affiliation":[{"name":"School of Electrical and Electronic Engineering, Chongqing University of Technology, Chongqing 400054, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3921-9152","authenticated-orcid":false,"given":"Fen","family":"Chen","sequence":"additional","affiliation":[{"name":"School of Electrical and Electronic Engineering, Chongqing University of Technology, Chongqing 400054, China"},{"name":"Faculty of Information Science and Engineering, Ningbo University, No. 818, Ningbo 315211, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8286-538X","authenticated-orcid":false,"given":"Zongju","family":"Peng","sequence":"additional","affiliation":[{"name":"School of Electrical and Electronic Engineering, Chongqing University of Technology, Chongqing 400054, China"},{"name":"Faculty of Information Science and Engineering, Ningbo University, No. 818, Ningbo 315211, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6065-5987","authenticated-orcid":false,"given":"Wenhui","family":"Zou","sequence":"additional","affiliation":[{"name":"Faculty of Information Science and Engineering, Ningbo University, No. 818, Ningbo 315211, China"}]},{"given":"Changhe","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Electrical and Electronic Engineering, Chongqing University of Technology, Chongqing 400054, China"}]}],"member":"1968","published-online":{"date-parts":[[2023,9,15]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Jeon, H.G., Park, J., Choe, G., Park, J., Bok, Y., Tai, Y.W., and So Kweon, I. 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