Title: Automatic contrast enhancement using Selective Grey-Level Grouping

Authors: Rekha Lakshmanan, Madhu S. Nair, M. Wilscy, Rao Tatavarti

Addresses: KMEA Engineering College, Aluva, Kerala, India. ' Department of Information Technology, Rajagiri School of Engineering and Technology, Kakkanad, Kochi 682039, Kerala, India. ' Department of Computer Science, University of Kerala, Karyavattom, Trivandrum, Kerala, India. ' VIT University, Vellore, Tamil Nadu, India

Abstract: In this paper, we introduce a method called Automatic Selective Grey-Level Grouping (ASGLG), which enables automatic contrast enhancement of an image based on the principle of transforming the skewed histogram of the original image into a uniform histogram after the recent work on Selective Grey-Level Grouping (SGLG) of the image by Chen et al. (2006a). In SGLG the user needs to specify the greyscale breakpoint and its new location on the greyscale, while the proposed ASLG is automatic and does not require user interface. The histogram based Grey-Level Grouping (GLG) method and its variants (after Chen et al., 2006b) and the Fuzzy Logic method (after Hanmandlu and Jha, 2006) are evaluated on different images in order to ascertain which of the algorithms are better suited across a variety of images from different sensors and having varying characteristics. Based on the visual quality and the Tenengrad criterion we conclude that the ASGLG yields better results.

Keywords: automatic contrast enhancement; GLG; grey-level grouping; skewed histograms; uniform histograms; quality measures; fuzzy logic; entropy; image enhancement; imaging systems.

DOI: 10.1504/IJSISE.2010.035001

International Journal of Signal and Imaging Systems Engineering, 2010 Vol.3 No.2, pp.126 - 135

Published online: 31 Aug 2010 *

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