{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T04:37:28Z","timestamp":1760243848477,"version":"build-2065373602"},"reference-count":27,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2011,8,29]],"date-time":"2011-08-29T00:00:00Z","timestamp":1314576000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/3.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Images from high dynamic range (HDR) scenes must be obtained with minimum loss of information. For this purpose it is necessary to take full advantage of the quantification levels provided by the CCD\/CMOS image sensor. LinLog CMOS sensors satisfy the above demand by offering an adjustable response curve that combines linear and logarithmic responses. This paper presents a novel method to quickly adjust the parameters that control the response curve of a LinLog CMOS image sensor. We propose to use an Adaptive Proportional-Integral-Derivative controller to adjust the exposure time of the sensor, together with control algorithms based on the saturation level and the entropy of the images. With this method the sensor\u2019s maximum dynamic range (120 dB) can be used to acquire good quality images from HDR scenes with fast, automatic adaptation to scene conditions. Adaptation to a new scene is rapid, with a sensor response adjustment of less than eight frames when working in real time video mode. At least 67% of the scene entropy can be retained with this method.<\/jats:p>","DOI":"10.3390\/s110908412","type":"journal-article","created":{"date-parts":[[2011,8,30]],"date-time":"2011-08-30T06:04:23Z","timestamp":1314684263000},"page":"8412-8429","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["A Novel Method to Increase LinLog CMOS Sensors\u2019 Performance in High Dynamic Range Scenarios"],"prefix":"10.3390","volume":"11","author":[{"given":"Antonio","family":"Mart\u00ednez-S\u00e1nchez","sequence":"first","affiliation":[{"name":"Supercomputing and Algorithms Group, CSIC-UAL Associated Unit, University of Almeria, 04120 Almeria, Spain"}]},{"given":"Carlos","family":"Fern\u00e1ndez","sequence":"additional","affiliation":[{"name":"DSIE, Universidad Polit\u00e9cnica de Cartagena, Campus Muralla del Mar, s\/n. E-30202 Cartagena, Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8367-2934","authenticated-orcid":false,"given":"Pedro J.","family":"Navarro","sequence":"additional","affiliation":[{"name":"DSIE, Universidad Polit\u00e9cnica de Cartagena, Campus Muralla del Mar, s\/n. E-30202 Cartagena, Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4308-1472","authenticated-orcid":false,"given":"Andr\u00e9s","family":"Iborra","sequence":"additional","affiliation":[{"name":"DSIE, Universidad Polit\u00e9cnica de Cartagena, Campus Muralla del Mar, s\/n. E-30202 Cartagena, Spain"}]}],"member":"1968","published-online":{"date-parts":[[2011,8,29]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Reinhard, E, Ward, G, Pattanaik, S, and Debevec, P (2006). High Dynamic Range Imaging: Acquisition, Display, and Image-Based Lighting, Elsevier\/Morgan Kaufmann.","DOI":"10.1016\/B978-012585263-0\/50010-5"},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Bandoh, Y, Qiu, G, Okuda, M, Daly, S, Aach, T, and Au, OC (2010, January 26\u201329). Recent Advances in High Dynamic Range Imaging Technology. Hong Kong, China.","DOI":"10.1109\/ICIP.2010.5653554"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"860","DOI":"10.3390\/s100100860","article-title":"Vision-based traffic data collection sensor for automotive applications","volume":"10","author":"Llorca","year":"2010","journal-title":"Sensors"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"2252","DOI":"10.3390\/s90402252","article-title":"Review: Visual sensor technology for advanced surveillance systems: Historical view, technological aspects and research activities in Italy","volume":"9","author":"Foresti","year":"2009","journal-title":"Sensors"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"7067","DOI":"10.3390\/s100807067","article-title":"A sensor system for detection of hull surface defects","volume":"10","author":"Navarro","year":"2010","journal-title":"Sensors"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"459","DOI":"10.1117\/1.1580829","article-title":"High dynamic range imaging for digital still camera: An overview","volume":"12","author":"Battiato","year":"2003","journal-title":"J. Electron. Imag"},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Brauers, J, Schulte, N, Bell, A, and Aach, T (2008). Multispectral High Dynamic Range Imaging, IS\/&T\/SPIE Electronic Imaging.","DOI":"10.1117\/12.761105"},{"key":"ref_8","unstructured":"Hazelwood, M, Hutton, S, and Weatherup, C Smear Reduction in CCD Images, US Patent 7,808,534, 2010."},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Burghartz, JN, Graf, H, Harendt, G, Klinger, W, Richter, H, and Strobel, M (2006, January 22\u201326). HDR CMOS Imagers and Their Applications. Shanghai, China.","DOI":"10.1109\/ICSICT.2006.306343"},{"key":"ref_10","unstructured":"Nayar, SK, and Mitsunaga, T (2000, January 13\u201315). High Dynamic Range Imaging: Spatially Varying Pixel Exposures. Hilton Head Island, SC, USA."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"433","DOI":"10.1016\/j.mejo.2005.07.002","article-title":"Review of CMOS image sensors","volume":"37","author":"Bigas","year":"2006","journal-title":"Microelectron. J"},{"key":"ref_12","unstructured":"Dumont, GA, and Huzmezan, M Concepts, methods and techniques in adaptive control."},{"key":"ref_13","unstructured":"Bela, L Instrument Engineers\u2019 Handbook: Process Control."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Mohan, M, and Sinha, A (2008, January 6\u201311). Mathematical Model of the Simplest Fuzzy PID Controller with Asymmetric Fuzzy Sets. Seoul, Korea.","DOI":"10.3182\/20080706-5-KR-1001.02604"},{"key":"ref_15","unstructured":"Cha\u00ednho, J, Pereira, P, Rafael, S, and Pires, AJ (July, January 30). A Simple PID Controller with Adaptive Parameter in a dsPIC: A Case of Study. Marbella, Spain."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"111","DOI":"10.1049\/ip-d.1991.0015","article-title":"Refinements of the Ziegler-Nichols tuning formula","volume":"138","author":"Hang","year":"1991","journal-title":"IEEE Proc. Control Theory Appl"},{"key":"ref_17","unstructured":"Navid, N, and Roberts, J (2007, January 10\u201312). Automatic Camera Exposure Control. Brisbane, Australia."},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Neves, JA, Cunha, B, Pinho, A, and Pinheiro, I (2009, January 10\u201312). Autonomous Configuration of Parameters in Robotic Digital Cameras. P\u00f3voa de Varzim, Portugal.","DOI":"10.1007\/978-3-642-02172-5_12"},{"key":"ref_19","unstructured":"Nilsson, M, Weerasinghe, C, Lichman, S, Shi, Y, and Kharitonenko, I (2003, January 6\u221210). Design and Implementation of a CMOS Sensor Based Video Camera Incorporating a Combined AWB\/AEC Module. Hong Kong, China."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"338","DOI":"10.1007\/s10278-007-9044-5","article-title":"Information entropy measure for evaluation of image quality","volume":"21","author":"Tsai","year":"2008","journal-title":"J Digital Imaging"},{"key":"ref_21","unstructured":"Shannon, CE, and Weaver, W (1949). The Mathematical Theory of Communication, University of Illinois Press."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Gray, RM (2010). Entropy and Information Theory, Springer-Verlag Inc. [2nd ed].","DOI":"10.1007\/978-1-4419-7970-4_3"},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Hendrix, EMT, and Toth, BG (2010). Introduction to Nonlinear and Global Optimization, Springer.","DOI":"10.1007\/978-0-387-88670-1"},{"key":"ref_24","unstructured":"Moneta, CA, de Natale, FGB, and Vernazza, G (1994, January 25\u201327). Adaptive Control in Visual Sensing. Lille, France."},{"key":"ref_25","unstructured":"Malis, E (May, January 26). Improving Vision-Based Control Using Efficient Second-Order Minimization Techniques. New Orleans, LA, USA."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"304","DOI":"10.1117\/12.533976","article-title":"B-spline registration of 3D images with levenberg-marquardt optimization","volume":"5370","author":"Kabus","year":"2004","journal-title":"Proc. SPIE"},{"key":"ref_27","unstructured":"LabVIEW (Laboratory Virtual Instrumentation Engineering Workbench) National Instruments Corporation: Austin, TX, USA. Available online: http:\/\/www.ni.com\/labview\/ (accessed on 10 August 2011)."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/11\/9\/8412\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T21:57:13Z","timestamp":1760219833000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/11\/9\/8412"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2011,8,29]]},"references-count":27,"journal-issue":{"issue":"9","published-online":{"date-parts":[[2011,9]]}},"alternative-id":["s110908412"],"URL":"https:\/\/doi.org\/10.3390\/s110908412","relation":{},"ISSN":["1424-8220"],"issn-type":[{"type":"electronic","value":"1424-8220"}],"subject":[],"published":{"date-parts":[[2011,8,29]]}}}