{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,20]],"date-time":"2026-03-20T00:16:19Z","timestamp":1773965779736,"version":"3.50.1"},"reference-count":22,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2025,6,9]],"date-time":"2025-06-09T00:00:00Z","timestamp":1749427200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100003032","name":"Association Nationale de la Recherche et de la Technologie","doi-asserted-by":"publisher","award":["2021\/1239"],"award-info":[{"award-number":["2021\/1239"]}],"id":[{"id":"10.13039\/501100003032","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["BDCC"],"abstract":"<jats:p>In image processing, the acquisition step plays a fundamental role because it determines image quality. The present paper focuses on the issue of blur and suggests ways of assessing contrast. The logic of this work consists in evaluating the sharpness of an image by means of objective measures based on mathematical, physical, and optical justifications in connection with the human visual system. This is why the Logarithmic Image Processing (LIP) framework was chosen. The sharpness of an image is usually assessed near objects\u2019 boundaries, which encourages the use of gradients, with some major drawbacks. Within the LIP framework, it is possible to overcome such problems using a \u201ccontour detector\u201d tool based on the notion of Logarithmic Additive Contrast (LAC). Considering a sequence of images increasingly blurred, we show that the use of LAC enables images to be re-classified in accordance with their defocus level, demonstrating the relevance of the method. The proposed algorithm has been shown to outperform five conventional methods for assessing image sharpness. Moreover, it is the only method that is insensitive to brightness variations. Finally, various application examples are presented, like automatic autofocus control or the comparison of two blur removal algorithms applied to the same image, which particularly concerns the field of Super Resolution (SR) algorithms. Such algorithms multiply (\u00d72, \u00d73, \u00d74) the resolution of an image using powerful tools (deep learning, neural networks) while correcting the potential defects (blur, noise) that could be generated by the resolution extension itself. We conclude with the prospects for this work, which should be part of a broader approach to estimating image quality, including sharpness and perceived contrast.<\/jats:p>","DOI":"10.3390\/bdcc9060154","type":"journal-article","created":{"date-parts":[[2025,6,9]],"date-time":"2025-06-09T09:13:01Z","timestamp":1749460381000},"page":"154","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Image Visual Quality: Sharpness Evaluation in the Logarithmic Image Processing Framework"],"prefix":"10.3390","volume":"9","author":[{"given":"Arnaud","family":"Pauwelyn","sequence":"first","affiliation":[{"name":"NT2I (Nouvelles Technologies Ing\u00e9nierie Innovation), 18, Rue Jean Servanton, 42000 Saint-Etienne, France"},{"name":"ICB (Laboratoire Interdisciplinaire Carnot de Bourgogne), CNRS, Universit\u00e9 Bourgogne Europe, 21078 Dijon, France"}]},{"given":"Maxime","family":"Carr\u00e9","sequence":"additional","affiliation":[{"name":"NT2I (Nouvelles Technologies Ing\u00e9nierie Innovation), 18, Rue Jean Servanton, 42000 Saint-Etienne, France"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2076-3465","authenticated-orcid":false,"given":"Michel","family":"Jourlin","sequence":"additional","affiliation":[{"name":"Laboratoire Hubert Curien, CNRS, Universit\u00e9 Jean Monnet, 18, Rue Professeur Beno\u00eet Lauras, 42000 Saint-Etienne, France"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5911-2010","authenticated-orcid":false,"given":"Dominique","family":"Ginhac","sequence":"additional","affiliation":[{"name":"ICB (Laboratoire Interdisciplinaire Carnot de Bourgogne), CNRS, Universit\u00e9 Bourgogne Europe, 21078 Dijon, France"}]},{"given":"Fabrice","family":"Meriaudeau","sequence":"additional","affiliation":[{"name":"IFTIM (Imagerie Fonctionnelle et mol\u00e9culaire et Traitement des Images M\u00e9dicales), ICMUB (Institut de Chimie Mol\u00e9culaire), CNRS, Universit\u00e9 de Bourgogne, 9, Avenue Alain Savary, 21078 Dijon, France"}]}],"member":"1968","published-online":{"date-parts":[[2025,6,9]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Zhu, M., Yu, L., Wang, Z., Ke, Z., and Zhi, C. 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