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

Authors
Yusuke Kawakami, Tetsuo Hattori, Yoshiro Imai, Yo Horikawa, Kazuaki Ando, R. P. C. Janaka Rajapakse
Corresponding Author
Yusuke Kawakami
Available Online 1 June 2016.
DOI
https://doi.org/10.2991/jrnal.2016.3.1.13
Keywords
Image processing, Histogram, Curvature, Variance estimation, Histogram matching, HMGD
Abstract
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.

Copyright
© 2013, the Authors. Published by ALife Robotics Corp. Ltd.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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