Joint image registration and super-resolution reconstruction based on regularized total least norm

Abstract

Accurate registration of the low resolution (LR) images is a critical step in image super resolution reconstruction (SRR). Conventional algorithms always use invariable motion parameters derived from registration algorithms, and carry on SRR without considering the registration errors in the disjointed method. In this paper we propose a new method that performs joint image registration and SRR based on regularized total least norm (RTLN), updating the motion parameters and HR image simultaneously. Not only translation but also rotation motion are considered, which makes the motion model more universal. Experimental results have shown that our approach is more effective and efficient than traditional ones.