Research on Blurred Image Restoration Quality Evaluation Method

Jian Hua Zhang; Fan Tao Kong; Jian Zhai Wu; Meng Shuai Zhu; Pu Zhao; Sheng Wei Wang

doi:10.4028/www.scientific.net/AMR.1049-1050.1698

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 1049-1050Research on Blurred Image Restoration Quality...

Research on Blurred Image Restoration Quality Evaluation Method

Abstract:

Accurate evaluation of image quality is always being a problem. With blurry cotton images as samples, using variance methods, average gradient method, gray prediction error statistics method and information entropy method, this research evaluated restoration quality of 4 kinds of images from the perspective of grayscale contrast, sharpness, contrast and ambiguity. The results show that the 4 image restoration algorithms all improved image quality, and Wiener algorithm improved image quality best comparing with other 3 algorithms, Reg second, Blind algorithm and K-L algorithm were worse.

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Periodical:

Advanced Materials Research (Volumes 1049-1050)

Pages:

1698-1702

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.1049-1050.1698

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Online since:

October 2014

Authors:

Jian Hua Zhang, Fan Tao Kong*, Jian Zhai Wu, Meng Shuai Zhu, Pu Zhao, Sheng Wei Wang

Keywords:

Blurred Image, Evaluation Method, Image Quality, Image Restoration

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* - Corresponding Author

References

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