8 February 2015 Intrinsic camera resolution measurement
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Abstract
Objective evaluation of digital image quality usually includes analysis of spatial detail in captured images. Although previously-developed methods and standards have found success in the evaluation of system performance, the systems in question usually include spatial image processing (e.g. sharpening or noise-reduction), and the results are influenced by these operations. Our interest, however, is in the intrinsic resolution of the system. By this we mean the performance primarily defined by the lens and imager, and not influenced by subsequent image processing steps that are invertible. Examples of such operations are brightness and contrast adjustments, and simple sharpening and blurring (setting aside image clipping and quantization). While these operations clearly modify image perception, they do not in general change the fundamental spatial image information that is captured. We present a method to measure an intrinsic spatial frequency response (SFR) computed from test image(s) for which spatial operations may have been applied. The measure is intended ‘see through’ operations for which image detail is retrievable but measure the loss of image resolution otherwise. We adopt a two-stage image capture model. The first stage includes a locally-stable point-spread function (lens), the integration and sampling by the detector (imager), and the introduction of detector noise. The second stage comprises the spatial image processing. We describe the validation of the method, which was done using both simulation and actual camera evaluations.
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Peter D. Burns, Peter D. Burns, Judit Martinez Bauza, Judit Martinez Bauza, } "Intrinsic camera resolution measurement", Proc. SPIE 9396, Image Quality and System Performance XII, 939609 (8 February 2015); doi: 10.1117/12.2083193; https://doi.org/10.1117/12.2083193
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