No-reference image sharpness assessment via difference quotients

12 February 2019 No-reference image sharpness assessment via difference quotients

Jiye Qian, Hengjun Zhao, Jin Fu, Wei Song, Jide Qian, Qianbo Xiao

Author Affiliations +

Funded by: Special Foundation for Chongqing Postdoctoral Research, Chongqing Research Program of Basic Research and Frontier Technology, National Natural Science Foundation of China (NSFC)

Journal of Electronic Imaging, Vol. 28, Issue 1, 013032 (February 2019). https://doi.org/10.1117/1.JEI.28.1.013032

Abstract

Sharpness is an important indicator to evaluate image quality or to optimize parameters in computer vision tasks, such as image acquisition, compression, and restoration. We utilize difference quotients to construct an absolute difference quotient and a relative difference quotient to evaluate the sharpness among images containing difference contents and the sharpness among pixels in the same image, respectively. Based on the constructed quotients, we estimate the pixel sharpness index and the image block sharpness index and create a single sharpness index as the overall sharpness of an image by pooling strategy. Our quotient-based methods can assess image sharpness effectively and efficiently. Experimental results on four simulated databases with real blurring and synthetic blurring images show the proposed sharpness metric is consistent with subjective sharpness evaluations and is competitive with existing sharpness metrics. It achieves a balance between running time and high performance.

Citation Download Citation

Jiye Qian, Hengjun Zhao, Jin Fu, Wei Song, Jide Qian, and Qianbo Xiao "No-reference image sharpness assessment via difference quotients," Journal of Electronic Imaging 28(1), 013032 (12 February 2019). https://doi.org/10.1117/1.JEI.28.1.013032

Received: 26 June 2018; Accepted: 7 January 2019; Published: 12 February 2019

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