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王俊琦, 张立国, 刘磊. 基于线扩散函数提取的无参考图像清晰度评价[J]. 计算机辅助设计与图形学学报, 2016, 28(8): 1279-1286.
引用本文: 王俊琦, 张立国, 刘磊. 基于线扩散函数提取的无参考图像清晰度评价[J]. 计算机辅助设计与图形学学报, 2016, 28(8): 1279-1286.
Wang Junqi, Zhang Liguo, Liu Lei. No-Reference Image Quality Assessment for Sharpness Based on Line Spread Function[J]. Journal of Computer-Aided Design & Computer Graphics, 2016, 28(8): 1279-1286.
Citation: Wang Junqi, Zhang Liguo, Liu Lei. No-Reference Image Quality Assessment for Sharpness Based on Line Spread Function[J]. Journal of Computer-Aided Design & Computer Graphics, 2016, 28(8): 1279-1286.

基于线扩散函数提取的无参考图像清晰度评价

No-Reference Image Quality Assessment for Sharpness Based on Line Spread Function

  • 摘要: 为了评价实际拍摄场景中图像的清晰度状况,提出一种无参考的质量评价方法.首先提取图像边缘并去除纹理复杂区域,得到可使用的边缘图;然后沿各边界点梯度方向作对应线扩散函数曲线,各点的线扩散函数半高全宽组成了清晰度参数集合;最后以集合的统计特性来分析图像清晰度变化情况.分别从图像与清晰度关系分析、算法稳定性、算法的抗噪声能力和离焦图像清晰度评价几个方面进行实验,结果表明,该方法能够评价图像的清晰度,不需要参考图像,评价结果具有良好的稳定性与抗噪声性能,具有广泛的应用价值.

     

    Abstract: A no-reference quality evaluation algorithm is presented in this paper, in order to estimate the sharpness of images in practice. Firstly, useful information is obtained by extracting edge from original images and removing their complex texture region. Then line spread function curves are plotted along the gradient direction of each edge pixel, so that their full width values at half maximum can form the sharpness parameter congregation. Finally, the changes of image sharpness can be known by analyzing that congregation’s static characteristics. Experiments are carried out in three aspects: the relationship between images and their sharpness, the algorithm’s stability and anti-noise capability, the sharpness assessing ability for defocus images. The results show that this algorithm is effective in sharpness evaluation in the case with no reference. Furthermore, it has high stability and noise-resist capacity, indicating extensive value for engineering application.

     

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