DocumentCode :
2833405
Title :
Automatic Contrast Enhancement for Low Contrast Images: A Comparison of Recent Histogram Based Techniques
Author :
Lakshmanan, Rekha ; Nair, Madhu S. ; Wilscy, M. ; Tatavarti, Rao
Author_Institution :
KMEA Eng. Coll., Aluva
fYear :
2008
fDate :
Aug. 29 2008-Sept. 2 2008
Firstpage :
269
Lastpage :
276
Abstract :
In this paper we compare two recent methods for automatic enhancement of the contrast of the image, based on the principle of transforming the skewed histogram of the original image into a uniform histogram. The histogram based gray level grouping (GLG) method and its variants (after Chen et al., 2006) and the fuzzy logic method (after Hanmandlu and Jha, 2006) are evaluated on three different images (gray scale as well as color) 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 FastHSV variant of the GLG method may be applied for automatic contrast enhancement across a wide variety of images.
Keywords :
fuzzy logic; image enhancement; Tenengrad criterion; automatic contrast enhancement; fuzzy logic; histogram based gray level grouping; histogram based technique; low contrast images; skewed histogram; uniform histogram; visual quality; Adaptive equalizers; Background noise; Computer science; Educational institutions; Fuzzy logic; Histograms; Image enhancement; Image sensors; Pixel; Sensor phenomena and characterization; Contrast enhancement; color images; entropy; fuzzy; gray-level grouping; histogram;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Science and Information Technology, 2008. ICCSIT '08. International Conference on
Conference_Location :
Singapore
Print_ISBN :
978-0-7695-3308-7
Type :
conf
DOI :
10.1109/ICCSIT.2008.16
Filename :
4624874
Link To Document :
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