{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,30]],"date-time":"2026-07-30T11:56:10Z","timestamp":1785412570896,"version":"3.56.0"},"reference-count":35,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2026,5,21]],"date-time":"2026-05-21T00:00:00Z","timestamp":1779321600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62073078"],"award-info":[{"award-number":["62073078"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"award":["62073078"],"award-info":[{"award-number":["62073078"]}],"id":[{"id":"https:\/\/ror.org\/01h0zpd94","id-type":"ROR","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012221","name":"Jinling Institute of Technology","doi-asserted-by":"publisher","award":["jit-b-202156"],"award-info":[{"award-number":["jit-b-202156"]}],"id":[{"id":"10.13039\/501100012221","id-type":"DOI","asserted-by":"publisher"}]},{"award":["jit-b-202156"],"award-info":[{"award-number":["jit-b-202156"]}],"id":[{"id":"https:\/\/ror.org\/05em1gq62","id-type":"ROR","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J. Imaging"],"abstract":"<jats:p>Accurate estimation of atmospheric light (AL) is essential within the atmospheric scattering model (ASM) to achieve high-quality image dehazing. Most existing methods, however, typically assume spatial uniformity of AL and rely on heuristic estimation from distant pixels, which often results in color distortion and exposure imbalance in dehazed outputs. To address this issue, we propose a novel framework that decouples AL into distinct color and intensity components. Specifically, a neutral pixel prior (NPP) is introduced for precise AL color estimation, which can eliminate color casts. For AL intensity estimation, an adaptive global-local fusion strategy integrating luminance perception transformation and a depth-related color prior (DRCP) is developed to realize balanced exposure. Extensive experiments demonstrate that the proposed method significantly outperforms state-of-the-art AL estimation methods, yielding dehazed images with enhanced color fidelity and more natural illumination.<\/jats:p>","DOI":"10.3390\/jimaging12050218","type":"journal-article","created":{"date-parts":[[2026,5,21]],"date-time":"2026-05-21T09:29:58Z","timestamp":1779355798000},"page":"218","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Adaptive Atmospheric Light Estimation for Dehazing via a Novel Decoupled Scattering Model with Neutral-Pixel and Visual-Depth Priors"],"prefix":"10.3390","volume":"12","author":[{"given":"Zhu","family":"Zhu","sequence":"first","affiliation":[{"name":"School of Computer Engineering, Jinling Institute of Technology, Nanjing 211169, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9961-6443","authenticated-orcid":false,"given":"Xiaoguo","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Instrument Science and Engineering, Southeast University, Nanjing 210096, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,5,21]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"5187","DOI":"10.1109\/TIP.2016.2598681","article-title":"Dehazenet: An end-to-end system for single image haze removal","volume":"25","author":"Cai","year":"2016","journal-title":"IEEE Trans. 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