A New No-reference Method for Color Image Quality Assessment
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10.5120/5073-7470 |
Sonia Ouni, Ezzeddine Zagrouba and Majed Chambah. Article: A New No-reference Method for Color Image Quality Assessment. International Journal of Computer Applications 40(17):24-31, February 2012. Full text available. BibTeX
@article{key:article,
author = {Sonia Ouni and Ezzeddine Zagrouba and Majed Chambah},
title = {Article: A New No-reference Method for Color Image Quality Assessment},
journal = {International Journal of Computer Applications},
year = {2012},
volume = {40},
number = {17},
pages = {24-31},
month = {February},
note = {Full text available}
}
Abstract
Image quality assessment (IQA) is a complex problem due to subjective nature of human visual perception. Human have always seen the world in color. The widely objective metrics used are mean squared error (MSE), peak signal to noise ratio (PSNR), and human visual system based on structural similarity and edge based similarity. The problem of these objective metrics that they evaluate the quality of grayscale images only and don’t make use of image color information. Also, we must have the presence of original image. Unfortunately, the field of no-reference (NR) color IQA has been largely unexplored although the color is a powerful descriptor that often simplifies the object identification and extraction from a scene so color information also could influence human beings’ judgments. So, in this paper a new no reference methods for color IQA are proposed. These methods are based on different statistical analyses and easy to calculate and applicable to various image processing. This proposed metrics are mathematically defined and overcame the limitations of existing metrics to assess the quality of the color in the image. The experiment results on various image distortion show that our proposed no reference metrics have a comparable performance to the other traditional error summation metrics and to the leading metrics available in literature.
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