1 March 2005 Influence of signal-to-noise ratio and point spread function on limits of superresolution
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Abstract
This paper presents a method to predict the limit of possible resolution enhancement given a sequence of low-resolution images. Three important parameters influence the outcome of this limit: the total Point Spread Function (PSF), the Signal-to-Noise Ratio (SNR) and the number of input images. Although a large number of input images captured by a system with a narrow PSF and a high SNR are desirable, these conditions are often not achievable simultaneously. To improve the SNR, cameras are designed with near optimal quantum efficiency and maximum fill-factor. However, the latter widens the system PSF, which puts more weight on the deblurring part of a super-resolution (SR) reconstruction algorithm. This paper analyzes the contribution of each input parameters to the SR reconstruction and predicts the best attainable SR factor for given a camera setting. The predicted SR factor agrees well with an edge sharpness measure computed from the reconstructed SR images. A sufficient number of randomly positioned input images to achieve this limit for a given scene can also be derived assuming Gaussian noise and registration errors.
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Tuan Quang Pham, Tuan Quang Pham, Lucas J. van Vliet, Lucas J. van Vliet, Klamer Schutte, Klamer Schutte, } "Influence of signal-to-noise ratio and point spread function on limits of superresolution", Proc. SPIE 5672, Image Processing: Algorithms and Systems IV, (1 March 2005); doi: 10.1117/12.586574; https://doi.org/10.1117/12.586574
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