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dc.contributor.authorSalem, Nema
dc.contributor.authorAsmaa Shams
dc.contributor.authorMalik, Hebatullah
dc.date.accessioned2023-03-15T07:41:24Z
dc.date.available2023-03-15T07:41:24Z
dc.date.issued2019
dc.identifier.citation61en_US
dc.identifier.doihttps://doi.org/10.1016/j.procs.2019.12.112en_US
dc.identifier.urihttp://hdl.handle.net/20.500.14131/672
dc.description.abstractMedical images constitute important information that clinicians need to diagnose and make the suitable treatment decisions. The diagnostic process extremely involves the image visual perception. Unfortunately, the possibility of error existence in perception is not acceptable as it mainly affects the patients’ lives. Image enhancement improves the visual quality of image, helps the clinician in his decision and thus saves the patients’ lives. Histogram is a common tool for improving contrast in medical imaging. It recovers the lost contrast by redistributing the image brightness values that unfortunately may generate undesirable artifacts. Therefore, researchers developed the histogram-based algorithms to overcome this problem. This paper presents a comprehensive study of many histogram-based algorithms. We utilized the powerful MATLAB package to analyze the enhancement performance of these histogram-based algorithms. Moreover, this paper quantitatively compares the results and thus evaluates their performance by three metric parameters, which are the mean square error, standard deviation, and the peak signal to noise ratioen_US
dc.publisherElsevieren_US
dc.subjectHistogram; Medical images; Enhancement; Contrast; Metric evaluation parameters; Peak signal to noise ratioen_US
dc.titleMedical image enhancement based on histogram algorithmsen_US
dc.contributor.researcherNo Collaborationen_US
dc.subject.KSAICTen_US
dc.contributor.ugstudentHebatullah Malik, and Asmaa Shamsen_US
dc.contributor.departmentElectrical and Computer Engineeringen_US
dc.contributor.firstauthorSalem, Nema
dc.conference.locationSaudi Arabiaen_US
dc.conference.name16th International Learning & Technology Conference 2019en_US
dc.conference.date2019-03-03


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