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衡量结构保持性能的SAR图像去噪质量评价

唐益明, 杨学志(合肥工业大学计算机与信息学院, 合肥 230009)

摘 要
现有相关图像质量评价方法均不能恰当衡量合成孔径雷达(SAR)图像去噪的结构保持性能,为此提出无参考的IENLR (improved equivalent number of looks of ratio image)评价方法。首先总结了已有的相关图像质量评价方法,分析其在衡量结构保持性能方面的局限性。随后,从比值图像的等效视数(ENLR)图像出发,构造了新评价方法IENLR的计算公式,并通过理论分析证明其为关于结构保持性能的基本单调、有界的函数,且具有参数的可调节性。最后,通过仿真实验进一步验证了IENLR的良好性能,并且发现IENLR在衡量结构保持性能方面优于现有的相关质量评价方法。
关键词
Image quality assessment of SAR image despeckling for measuring structure-preserving capability

Tang Yiming, Yang Xuezhi(School of Computer and Information, Hefei University of Technology, Hefei 230009, China)

Abstract
Currently, related image quality assessment methods can not appropriately measure structure-preserving capability of synthetic aperture radar (SAR) image despeckling, to solve this problem a no-reference improved equivalent number of looks of ratio image(IENLR) assessment method is put forward. To begin with, related image quality assessment methods are reviewed, where their weaknesses to measure structure-preserving capability are investigated. Furthermore, from equivalent number of looks of ratio(ENLR) image as a point of departure, the computing formula of IENLR is constructed, meanwhile theory analyses prove that IENLR is a basically monotone, bounded function with regard to structure-preserving capability, and that IENLR is adjustable in the light of its parameter. Finally, simulated experiments further verify that IENLR is excellent and superior to other related image quality assessment methods from the viewpoint of measuring structure-preserving capability.
Keywords

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