Enhancement of Low-Quality Images using Bi-Histogram Equalization adaptive sigmoid function based on Shifted Gomphertz Distribution

Authors

  • Sandeep Department of Computer Science, Kuvempu University, Shimoga, India
  • Suresha M Department of Computer Science, Kuvempu University, Shimoga, India

DOI:

https://doi.org/10.26438/ijcse/v7i1.185191

Keywords:

BBHE, Sigmoid function, Shifted Gomphertz Distribution, Under-water images

Abstract

Image enhancement participate crucial role in image processing area and its main agenda is improves visual quality of an image. Histogram equalization is most prevalent method in contrast enhancement. But its major drawback is overenhancement, therefore, it generates abnormal appearance. In this paper, proposed a method that solve over brightness problem by separate two histograms based on mean values of V-channel or intensity channel of HSV image. To calculate cumulative density function for each sub-histogram with two sigmoid function with their origins placed on the medians of sub-histogram after Shifted Gomphertz Distribution applied for each sub-histogram and equalized independently using histogram equalization. Experimental results demonstrate that proposed method gives good results compare to other state-of-the-arts methods with respect to over-enhancement.

References

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Published

2019-01-31
CITATION
DOI: 10.26438/ijcse/v7i1.185191
Published: 2019-01-31

How to Cite

[1]
Sandeep and M. Suresha, “Enhancement of Low-Quality Images using Bi-Histogram Equalization adaptive sigmoid function based on Shifted Gomphertz Distribution”, Int. J. Comp. Sci. Eng., vol. 7, no. 1, pp. 185–191, Jan. 2019.

Issue

Vol. 7 No. 1 (2019): IJCSE January Edition

Section

Research Article

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