KEYWORDS: Visualization, Linear filtering, Image filtering, Lab on a chip, Image quality, Spatial frequencies, LCDs, RGB color model, Color difference, Visual process modeling
Perceived image contrast is one of the major factors affecting the image quality on displays. Various methods have been
proposed to measure the image contrast. However, image contrasts in most of previous works are focused on B/W and
defined on simple patterns such as sinusoidal grating. This paper introduces a perceived contrast evaluation model for
natural color images. In pursuit of high accuracy, both global and local contrasts are taken into account. Global contrast
indicates difference in the perceived luminance and chroma. Local contrast describes the distinguishable degree in image
details. In the proposed method, global contrast is calculated based on the dynamic ranges in lightness and chroma. Local
contrast is obtained by gradient computations. Both of the global and local contrasts are merged to achieve the perceived
contrast. Two types of performance evaluations are performed. They are cross content and within content evaluations.
Results of experiments show that global contrast is more effective in the cross content evaluation where the contrast
differences between different natural color images are examined. For both of the cross and within content evaluations,
the proposed measure yields high value of correlation coefficient with the subjective scores from human visual tests.
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