Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/485094
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dc.coverage.spatialOptimization of pixel performance in cmos image sensors for computational photography
dc.date.accessioned2023-05-23T14:39:11Z-
dc.date.available2023-05-23T14:39:11Z-
dc.identifier.urihttp://hdl.handle.net/10603/485094-
dc.description.abstractCurrent image denoising systems use field programmable gate newlinearray (FPGA) hardware platforms to achieve speed and efficiency, which are newlinecritical in real-time applications, to eliminate numerous causes of digital newlineimage noise. Image denoising on these platforms, on the other hand, is subject newlineto ongoing innovation in order to provide the best denoising performance newlinepossible. Continuously expanding demand for image processing devices that newlinecan combine high-resolution with low-power sensing, especially compression. newlineImages can be captured and processed simultaneously using CMOS newlinesensors that incorporate both image sensing and processing capabilities, newlineparticularly the capacity to compress images. Object recognition and image newlineclassification require high-quality images, and CMOS image sensors with newlinehigh resolution/speed fill that need. Deep learning (DL) models have made newlinesignificant progress in the area of image classification newline
dc.format.extentxv,130
dc.languageEnglish
dc.relationp.115-129
dc.rightsuniversity
dc.titleOptimization of pixel performance in cmos image sensors for computational photography
dc.title.alternative
dc.creator.researcherVinayagam, P
dc.subject.keywordEngineering and Technology
dc.subject.keywordComputer Science
dc.subject.keywordComputer Science Information Systems
dc.description.note
dc.contributor.guideAnandan, P
dc.publisher.placeChennai
dc.publisher.universityAnna University
dc.publisher.institutionFaculty of Information and Communication Engineering
dc.date.registered
dc.date.completed2022
dc.date.awarded2022
dc.format.dimensions21cm
dc.format.accompanyingmaterialNone
dc.source.universityUniversity
dc.type.degreePh.D.
Appears in Departments:Faculty of Information and Communication Engineering

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01_title.pdfAttached File53.23 kBAdobe PDFView/Open
02_prelimpage.pdf2.88 MBAdobe PDFView/Open
03_content.pdf9.76 kBAdobe PDFView/Open
04_abstract.pdf13.1 kBAdobe PDFView/Open
05_chapter1.pdf21.82 MBAdobe PDFView/Open
06_chapter2.pdf239.21 kBAdobe PDFView/Open
07_chapter3.pdf5.23 MBAdobe PDFView/Open
08_chapter4.pdf6.64 MBAdobe PDFView/Open
09_chapter5.pdf2.88 MBAdobe PDFView/Open
10_annexure.pdf115.36 kBAdobe PDFView/Open
80_recommendation.pdf83.65 kBAdobe PDFView/Open


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