Please use this identifier to cite or link to this item: https://gnanaganga.inflibnet.ac.in:8443/jspui/handle/123456789/14994
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dc.contributor.authorMaik, Vivek-
dc.contributor.authorCho, Dohee-
dc.contributor.authorShekhar, R-
dc.contributor.authorHaldodderi, Sudhindra-
dc.contributor.authorPaik, Joonki-
dc.date.accessioned2024-03-30T10:11:02Z-
dc.date.available2024-03-30T10:11:02Z-
dc.date.issued2012-
dc.identifier.isbn9781467317191-
dc.identifier.isbn9781467317207-
dc.identifier.issn2375-1282-
dc.identifier.urihttps://doi.org/10.1109/NUICONE.2012.6493254-
dc.identifier.urihttp://gnanaganga.inflibnet.ac.in:8080/jspui/handle/123456789/14994-
dc.description.abstractA digital image usually has 8 bits of depth basically representing pixel intensity ranging for [0 255]. These pixel ranges allow 256 step levels of pixel values in the image. Thus the grayscale value for a given image is an integer. When we carry out interpolation of a given image for down sampling we have to round the interpolated value to integer which can result in loss of quality on perceived color values. This paper proposes a new method for recovering this loss of information during interpolation process. By using the proposed method the pixels tend to regain more original values which yields better looking images on down sampling.en_US
dc.language.isoenen_US
dc.publisher3Rd Nirma University International Conference on Engineering (Nuicone 2012)en_US
dc.publisherIEEEen_US
dc.subjectDigital Photographyen_US
dc.subjectImage Processingen_US
dc.subjectBit-Depthen_US
dc.subjectResizingen_US
dc.subjectBilinear Interpolationen_US
dc.subjectMoire Effecten_US
dc.subjectCurvesen_US
dc.subjectSpatial Frequency Responseen_US
dc.titleRecycling of Histogram Bins for Improving Image Contrasten_US
dc.typeArticleen_US
Appears in Collections:Conference Papers

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