Adaptive Sparse Constraint Image Super-Resolution Reconstruction Method
Liang Xiuju · Video Engineering · 2012
In this paper,sparse dictionary constraint based image SR method is briefly introduced and an adaptive fast reconstruction method based on the K-Means clustering is presented to reduce the reconstruction computation complexity.The proposed SR reduces its complexity from two aspects.First,the dictionary size for each image patch in the learning process is reduced by classifying the sampled raw patches in the dictionary training process.Second,the reconstruction algorithm according to the features existed in each patch is adaptively selected.Experimental results show that the proposed fast reconstruction method takes much less time while generating images equivalent to the original algorithm.