• Textile Coloration and Finishing
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• v.9 no.6
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• pp.51-57
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• 1997

The lightness, chroma and hue tolerances with respect to the standard colour position in the CIELAB space have been studied in detail using the various existing data sets and the set form this study. The lightness tolerance showed a clear dependency upon the metric lightness for medium to light colour, but in the case of dark colours there was a discrepancy between the data sets. Both the chroma and hue tolerances showed dependency upon both the chroma and hue-angle and not the single dependency upon the metric chroma, as assumed in the CIE94 formula. New weighting functions were derived from the above experimental evidence, and finally a new formula, LCD(Leeds Colour Difference) was proposed. The LCD formula is nearly as simple and flexible as CIE94 but smoothes the individual weighting functions, especially for lightness tolerances for light colours and chromaticity discrimination near the blue region.

• Journal of Electrical Engineering and Technology
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• v.10 no.3
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• pp.1233-1243
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• 2015

The contrast enhancement is great challenge in the image processing when images are suffering from poor contrast problem. Therefore, in order to overcome this problem an automatic method is proposed for contrast enhancement of natural color images. The proposed method consist of two stages: in first stage lightness component in YIQ color space is normalized by sigmoid function after the adaptive histogram equalization is applied on Y component and in second stage automatic color contrast enhancement algorithm is applied on output of the first stage. The proposed algorithm is tested on different NASA color images, hyperspectral color images and other types of natural color images. The performance of proposed algorithm is evaluated and compared with the other existing contrast enhancement algorithms in terms of colorfulness metric and color enhancement factor. The higher values of colorfulness metric and color enhancement factor imply that the visual quality of the enhanced image is good. Simulation results demonstrate that proposed algorithm provides higher values of colorfulness metric and color enhancement factor as compared to other existing contrast enhancement algorithms. The proposed algorithm also provides better visual enhancement results as compared with the other existing contrast enhancement algorithms.

• Science of Emotion and Sensibility
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• v.20 no.1
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• pp.57-66
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• 2017

Emotional image quality optimization methodologies are investigated using technological image quality controls based on the eye tests of various image samples. The images are evaluated based on various contrast, lightness and saturation image quality metric tone curves. The order of importance to image quality enhancements is contrast, saturation and brightness. The slopes of emotional image qualities with respect to technical image quality metric changes are found to be composed of mathematical function modelling with nearly zero, intermediate and maximum slope regions in general, which can reflect well known log and saturated as well as conventional reverse U shape natures. Image quality improvements are analyzed not only with just single but also with multiple image quality metrics. To ease the unified image quality metric analysis and control, a new function is presented to utilize both the newly found and conventional emotional image quality behaviors. It is found that the overall image quality enhancement can be realized only in a few limited cases of multiple image quality metric controls. It is also found that the kinds of image quality enhancement methodologies are not strongly dependent on image contents (genre).