Abstract:
Images captured under low-light conditions are noisy as a result of photon statistics and quantization error, among other reasons. Such statistical limitations can be red...Show MoreMetadata
Abstract:
Images captured under low-light conditions are noisy as a result of photon statistics and quantization error, among other reasons. Such statistical limitations can be reduced by using pixels with larger areas, but this approach leads to aliasing artifacts. We propose a maximum-likelihood version of super-resolution for low-light conditions in which Fourier image coefficients and unknown spatial shifts between captured frames are estimated iteratively, all in order to produce the single image with high expected fidelity. We illustrate the power of our method on both one-dimensional synthetic data and on two-dimensional medical images.
Published in: 2013 IEEE International Conference on Image Processing
Date of Conference: 15-18 September 2013
Date Added to IEEE Xplore: 13 February 2014
Electronic ISBN:978-1-4799-2341-0