Standard Intensity Deviation based Recursive Histogram Equalization Contrast Enhancement for Low-exposure Images

The low exposure images pose challenges in better visibility due to its low light conditions. The visibility can be improved by contrast enhancement.  To improve image contrast, the histogram equalization (HE) is a famous method.  The existing HE based algorithm for low exposure images leads to an over enhancement problem and unnatural appearance. In this framework, the generalized algorithm proposed for contrast improvement, it performs the separation of the histogram based on respective standard intensity deviation value and then recursively equalizes all sub histograms independently. The over-enhancement problem is minimized by this method. Added to this, the presented methodology preserves image information and increases image brightness adaptively. A total of 150 low exposure images are used to evaluate its performance and compared it with several existing state-of-the-art algorithms. The experiment results are analyzed in terms of entropy, absolute mean brightness error (AMBE), degree of entropy un-preservation (DEU) and output image inspection. The proposed method results show significant improvement in enhancing low exposure images.

Author (s) Details

Dr. K. S. Sandeepa
Department of Electronics, Kuvempu University, Jnanasahyadri, Shimoga, India.

Dr. Basavaraj N. Jagadale

Department of Electronics, Kuvempu University, Jnanasahyadri, Shimoga, India.

Prof. J. S. Bhat
Indian Institute of Information Technology, Surat, India.

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