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图像质量的客观评估。II. 费舍尔信息、傅里叶串扰及任务性能的品质因数。

Objective assessment of image quality. II. Fisher information, Fourier crosstalk, and figures of merit for task performance.

作者信息

Barrett H H, Denny J L, Wagner R F, Myers K J

机构信息

Department of Radiology and Optical Sciences Center, University of Arizona, Tucson 85724, USA.

出版信息

J Opt Soc Am A Opt Image Sci Vis. 1995 May;12(5):834-52. doi: 10.1364/josaa.12.000834.

Abstract

Figures of merit for image quality are derived on the basis of the performance of mathematical observers on specific detection and estimation tasks. The tasks include detection of a known signal superimposed on a known background, detection of a known signal on a random background, estimation of Fourier coefficients of the object, and estimation of the integral of the object over a specified region of interest. The chosen observer for the detection tasks is the ideal linear discriminant, which we call the Hotelling observer. The figures of merit are based on the Fisher information matrix relevant to estimation of the Fourier coefficients and the closely related Fourier crosstalk matrix introduced earlier by Barrett and Gifford [Phys. Med. Biol. 39, 451 (1994)]. A finite submatrix of the infinite Fisher information matrix is used to set Cramer-Rao lower bounds on the variances of the estimates of the first N Fourier coefficients. The figures of merit for detection tasks are shown to be closely related to the concepts of noise-equivalent quanta (NEQ) and generalized NEQ, originally derived for linear, shift-invariant imaging systems and stationary noise. Application of these results to the design of imaging systems is discussed.

摘要

图像质量的品质因数是根据数学观察者在特定检测和估计任务中的表现得出的。这些任务包括检测叠加在已知背景上的已知信号、检测随机背景上的已知信号、估计物体的傅里叶系数以及估计物体在指定感兴趣区域上的积分。用于检测任务的选定观察者是理想线性判别器,我们称之为霍特林观察者。品质因数基于与傅里叶系数估计相关的费希尔信息矩阵以及巴雷特和吉福德 [《物理医学与生物学》39, 451 (1994)] 之前引入的密切相关的傅里叶串扰矩阵。无限费希尔信息矩阵的有限子矩阵用于设置前N个傅里叶系数估计方差的克拉美 - 罗下界。检测任务的品质因数被证明与噪声等效量子 (NEQ) 和广义NEQ的概念密切相关,最初是为线性、平移不变成像系统和静止噪声推导出来的。讨论了这些结果在成像系统设计中的应用。

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