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Image gathering and digital restoration

1996; Royal Society; Volume: 354; Issue: 1716 Linguagem: Inglês

10.1098/rsta.1996.0099

1471-2962

Carl L. Fales, Friedrich O. Huck, Rachel Alter-Gartenberg, Zia-ur Rahman,

Random lasers and scattering media

Restricted accessMoreSectionsView PDF ToolsAdd to favoritesDownload CitationsTrack Citations ShareShare onFacebookTwitterLinked InRedditEmail Cite this article Fales Carl L. , Huck Friedrich O. , Alter-Gartenberg Rachel and Rahman Zia-ur 1996Image gathering and digital restorationPhil. Trans. R. Soc. A.3542249–2287http://doi.org/10.1098/rsta.1996.0099SectionRestricted accessArticleImage gathering and digital restoration Carl L. Fales Google Scholar Find this author on PubMed Search for more papers by this author , Friedrich O. Huck Google Scholar Find this author on PubMed Search for more papers by this author , Rachel Alter-Gartenberg Google Scholar Find this author on PubMed Search for more papers by this author and Zia-ur Rahman Google Scholar Find this author on PubMed Search for more papers by this author Carl L. Fales Google Scholar Find this author on PubMed , Friedrich O. Huck Google Scholar Find this author on PubMed , Rachel Alter-Gartenberg Google Scholar Find this author on PubMed and Zia-ur Rahman Google Scholar Find this author on PubMed Published:15 October 1996https://doi.org/10.1098/rsta.1996.0099AbstractThis paper seeks to unite two disciplines: the electro-optical design of image gathering and display devices and the digital processing for image restoration. So far, these two disciplines have remained independent, following distinctly separate traditions. However, the best possible performance can be attained only when the digital processing algorithm accounts for the critical limiting factors of image gathering and display and the image-gathering device is designed to enhance the performance of the digital-processing algorithm. The following salient advantages accrue: 1. Spatial detail as fine as the sampling interval of the image-gathering device ordinarily can be restored sharply and clearly. 2. Even finer spatial detail than the sampling interval can be restored by combining a multiresponse image-gathering sequence with a restoration filter that properly reassembles the within-passband and aliased signal components. 3. The visual quality produced by traditional image gathering (e.g. television camera) and reconstruction (e.g. cubic convolution) can be improved with a small-kernel restoration operator without an increase in digital processing. 4. The enhancement of radiance-field transitions can be improved for dynamicrange compression (to suppress shadow obscurations) and for edge detection (for computer vision).FootnotesThis text was harvested from a scanned image of the original document using optical character recognition (OCR) software. As such, it may contain errors. Please contact the Royal Society if you find an error you would like to see corrected. Mathematical notations produced through Infty OCR. Previous Article VIEW FULL TEXT DOWNLOAD PDF FiguresRelatedReferencesDetailsCited by Kumar S and Kumar R (2022) Intelligent model to image enrichment for strong night-vision surveillance cameras in future generation, Multimedia Tools and Applications, 10.1007/s11042-022-12496-w, 81:12, (16335-16351), Online publication date: 1-May-2022. Jiang B (2012) Information theoretic analysis of linear shift-invariant edge-detection operators, Optical Engineering, 10.1117/1.OE.51.6.067013, 51:6, (067013), Online publication date: 19-Jun-2012. Huck F and Fales C (2005) Information Theory in Imaging Encyclopedia of Modern Optics, 10.1016/B978-0-12-809283-5.00708-4, (175-186), . Huck F and Fales C (2005) IMAGING | Information Theory in Imaging Encyclopedia of Modern Optics, 10.1016/B0-12-369395-0/00708-9, (107-117), . Alter-Gartenberg R, Nolf S and Davis R (2002) Assessment of the Wiener–Retinex process, Applied Optics, 10.1364/AO.41.004783, 41:23, (4783), Online publication date: 10-Aug-2002. Huck F and Fales C (2002) Characterization of Image Systems Encyclopedia of Imaging Science and Technology, 10.1002/0471443395.img004 Abshire P and Andreou A (2001) Capacity and energy cost of information in biological and silicon photoreceptors, Proceedings of the IEEE, 10.1109/5.939817, 89:7, (1052-1064), Online publication date: 1-Jul-2001. Rahman Z (2001) Information capacity of sampling-limited systems Integrated Computational Imaging Systems, 10.1364/ICIS.2001.IWA3, 1-55752-688-5, (IWA3) Alter-Gartenberg R (2000) Information metric as a design tool for optoelectronic imaging systems, Applied Optics, 10.1364/AO.39.001743, 39:11, (1743), Online publication date: 10-Apr-2000. Huck F, Fales C, Davis R and Alter-Gartenberg R (2000) Visual communication with retinex coding, Applied Optics, 10.1364/AO.39.001711, 39:11, (1711), Online publication date: 10-Apr-2000. Huck F (1999) Information-theoretic assessment of sampled imaging systems, Optical Engineering, 10.1117/1.602264, 38:5, (742), Online publication date: 1-May-1999. Park S (1999) Fidelity analysis of sampled imaging systems, Optical Engineering, 10.1117/1.602047, 38:5, (786), Online publication date: 1-May-1999. Huck F, Fales C and Rahman Z (1997) Introduction Visual Communication, 10.1007/978-1-4757-2568-1_1, (1-12), . Huck F, Fales C and Rahman Z On the information-theoretic assessment of visual communication 3rd IEEE International Conference on Image Processing, 10.1109/ICIP.1996.560873, 0-7803-3259-8, (437-440) This Issue15 October 1996Volume 354Issue 1716 Article InformationDOI:https://doi.org/10.1098/rsta.1996.0099Published by:Royal SocietyPrint ISSN:1364-503XOnline ISSN:1471-2962History: Published online01/01/1997Published in print15/10/1996 License:Scanned images copyright © 2017, Royal Society Citations and impact