Tuan Q. Pham, Lucas J. van Vliet, Klamer Schutte. Influence of signal-to-noise ratio and point spread function on limits of superresolution. In Edward R. Dougherty, Jaakko Astola, Karen O. Egiazarian, editors, Image Processing: Algorithms and Systems IV, 17 January 2006, San Jose, California, USA. Volume 5672 of SPIE Proceedings, pages 169-180, SPIE, 2006. [doi]
This paper presents a method to predict the limit of possible resolution enhancement given a sequence of lowresolution 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.