Influence of Signal-to-Noise Ratio and Point Spread Function on Limits of Super-Resolution
conference paper
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.
Topics
TNO Identifier
222790
ISSN
0277786X
Publisher
SPIE
Source title
Proceedings of SPIE-IS and T Electronic Imaging - Image Processing: Algorithms and Systems IV, 17 January 2005 through 18 January 2005, San Jose, CA, USA
Editor(s)
Dougherty, E.R.
Astola, J.T.
Egiazarian, K.O.
Astola, J.T.
Egiazarian, K.O.
Place of publication
Bellingham, WA
Pages
169-180
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