Reproduction of more pleasing colors is one of the efficient methods to improve image quality of color imaging devices. A psychophysical experiment was completed to investigate the preferred colors for three main categories: human skin, blue sky and green grass. A new experimental technique, the cube-selection method, was developed to adjust lightness, chroma and hue to find out observer’s preference in CIELAB color space. It is a fast and accurate multi-dimensional adjustment technique superior to the conventional method of adjustment. Several potential influence factors for image color preference including image content, capturing illuminant, object background and culture difference were studied by comparing the observers’ preference. Applicable conclusions were drawn from the analysis of the experiment results that help better understand the influence of these factors. It showed that capturing illuminant and image content had significant influence for human skin and grass color reproduction preference respectively. The results from this paper show the way for further research on influence factors of color preference in photographic color reproduction.
KEYWORDS: Image quality, Colorimetry, Imaging systems, Image quality standards, Data modeling, Digital cameras, Image analysis, CRTs, Color reproduction, Digital imaging
Image noise is one of the important image quality metrics for evaluation and optimization in color reproduction system. While the noise evaluation in psychometric lightness L* works pretty well in black-and-white images, it is insufficient for color images. A perceptual color noise evaluation equation was derived to extend noise evaluation in CIELAB color space, incorporating chromatic noise components. Psychophysical experiments were designed to evaluate color noise subjectively. In the first step, Weber's Law and Fechner's Law were used to generate a standard ruler with equal perceptual interval steps, which served to anchor a numerical image quality rating scale for the subjective rating experiment in the second step. An objective noise evaluation equation that incorporated the noise sensitivity functions modeled from the experimental data was found to better correlate with subjective evaluation. A more robust noise evaluation equation will be derived based on the psychophysical experiment techniques and experimental data in the future.
Conference Committee Involvement (6)
Digital Photography and Mobile Imaging XI
9 February 2015 | San Francisco, California, United States
Digital Photography X
3 February 2014 | San Francisco, California, United States
Digital Photography IX
4 February 2013 | Burlingame, California, United States
Digital Photography VIII
23 January 2012 | Burlingame, California, United States
Digital Photography VII
24 January 2011 | San Francisco Airport, California, United States
Digital Photography VI
18 January 2010 | San Jose, California, United States
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