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
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