Automated Processing of Multiple-Brightness Peak Histogram Image Using Curvature and Variance Estimation

Previously, we have illustrated that the Histogram Matching based on Gaussian Distribution (HMGD) is an effective automated image processing method for obtaining a better feeling impression image. However, the simple HMGD works only for the image whose histogram has just one peak. For the image whos...

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Bibliographic Details
Published inJournal of robotics, networking and artificial life Vol. 3; no. 1; pp. 55 - 60
Main Authors Kawakami, Yusuke, Hattori, Tetsuo, Imai, Yoshiro, Horikawa, Yo, Ando, Kazuaki, Janaka Rajapakse, R. P. C.
Format Journal Article
LanguageEnglish
Published Dordrecht Springer Netherlands 2016
Subjects
Research Article
Histogram matching
Histogram
HMGD
Image processing
Variance estimation
Curvature
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Summary:Previously, we have illustrated that the Histogram Matching based on Gaussian Distribution (HMGD) is an effective automated image processing method for obtaining a better feeling impression image. However, the simple HMGD works only for the image whose histogram has just one peak. For the image whose histogram has multiple-brightness peak, it does not work as in the case of single peak histogram image. In this paper, we propose the improved method for multiple-brightness peak (HMGD-MBP). This method can not only detect multiple peaks but also estimate the variance of Gaussian distribution at each detected peak in the image histogram, using curvature computation. This paper also presents the effectiveness of the proposed method by showing the experimental results.
ISSN:2405-9021
2352-6386
DOI:10.2991/jrnal.2016.3.1.13