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Proceedings Paper

Histogram equalization of color images using the adaptive neighborhood approach
Author(s): Vasile V. Buzuloiu; Mihai Ciuc; Rangaraj M. Rangayyan; Loic Kij; Constantin Vertan
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Paper Abstract

Histogram equalization (HE) is one of the simplest and most effective techniques for enhancing gray-level images. For color images, HE becomes a more difficult task, due to the vectorial nature of data. We propose a new method for color image enhancement that uses two hierarchical levels of HE: global and local. In order to preserve the hue, equalization is only applied to intensities. For each pixel (called the 'seed' when processed) a variable-sized, variable-shaped neighborhood is determined to contain pixels that are 'similar' to the seed. Then, the histogram of the region is stretched in a range that is computed with respect to the statistical parameters of the region (mean, variance) and to the global HE function (of intensities), and only the seed will be given a new intensity value. We applied the proposed color HE method to various images and observed the results to be subjectively 'pleasant to the human eye,' with emphasized details, preserved colors, and with the histogram of intensities close to the ideal uniform one. The results compared favorably to those of three other methods (histogram explosion, histogram decimation, and three-dimensional histogram equalization) in terms of subjective visual quality.

Paper Details

Date Published: 5 March 1999
PDF: 9 pages
Proc. SPIE 3646, Nonlinear Image Processing X, (5 March 1999); doi: 10.1117/12.341099
Show Author Affiliations
Vasile V. Buzuloiu, Univ. Politehnica Bucuresti (Romania)
Mihai Ciuc, Univ. Politehnica Bucuresti (Romania)
Rangaraj M. Rangayyan, Univ. of Calgary (Canada)
Loic Kij, Univ. Politehnica Bucuresti (Romania)
Constantin Vertan, Univ. Politehnica Bucuresti (Romania)


Published in SPIE Proceedings Vol. 3646:
Nonlinear Image Processing X
Edward R. Dougherty; Jaakko T. Astola, Editor(s)

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