Please use this identifier to cite or link to this item: http://nopr.niscair.res.in/handle/123456789/58085
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dc.contributor.authorD, Vijayalakshmi-
dc.contributor.authorElangovan, Poonguzhali-
dc.contributor.authorNath, Malaya Kumar-
dc.date.accessioned2021-09-09T10:42:26Z-
dc.date.available2021-09-09T10:42:26Z-
dc.date.issued2021-03-
dc.identifier.issn0975-105X (Online); 0367-8393 (Print)-
dc.identifier.urihttp://nopr.niscair.res.in/handle/123456789/58085-
dc.description5-11en_US
dc.description.abstractThe quality of the MRI brain images is dependent on the sensor. It is essential to have a pre-processing technique to meet the finest quality at the sensor’s cost. A pre-processing algorithm has been proposed in this paper to enhance the low contrast MRI brain images. The input image’s histogram has been divided into two sub histograms using its median value to uphold the input image’s mean brightness. After calculating the Renyi entropy from the sub histogram, histogram clipping has been done to regulate the enhancement rate. The clipping limit has been selected automatically from the minimum value of the mean, median of the distribution function, and itself. Additionally, the proposed algorithm has incorporated the Discrete Cosine Transform (DCT) to improve the enhancement. Experimental results have shown that the proposed algorithm enhances the input image and maintains the mean brightness.en_US
dc.language.isoenen_US
dc.publisherNIScPR-CSIR, Indiaen_US
dc.sourceIJRSP Vol.50(1) [March 2021]en_US
dc.subjectAdaptive clipping limiten_US
dc.subjectContrast improvement indexen_US
dc.subjectDiscrete cosine transformen_US
dc.subjectGradient magnitude similarity deviationen_US
dc.subjectSpatial distributionen_US
dc.titleRenyi entropy based Bi-histogram equalization for contrast enhancement of MRI brain imagesen_US
dc.typeArticleen_US
Appears in Collections:IJRSP Vol.50(1) [March 2021]

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