Title :
Color image super-resolution reconstruction based on IMED
Author_Institution :
Sch. of Commun., Shandong Normal Univ., Jinan, China
Abstract :
In this paper, a novel color image super-resolution reconstruction algorithm based on IMage Euclidean Distance (IMED) and manifold learning is proposed. Firstly, the wavelet decomposition is used to extract features from training images. Then IMED is adopted for the computation of distances between pairs of small patches. Finally, the color high resolution image is reconstructed in YCbCr space in the framework of locally linear embedding. Experimental results demonstrate that the proposed method has better performance in comparison with the manifold learning method that is not combined with IMED.
Keywords :
feature extraction; image colour analysis; image reconstruction; image resolution; learning (artificial intelligence); wavelet transforms; YCbCr space; color image super-resolution reconstruction algorithm; feature extraction; image Euclidean distance; manifold learning; wavelet decomposition; Artificial intelligence; Image resolution; Manganese; Pixel; IMage Euclidean Distance (IMED); color super-resolution; manifold learning;
Conference_Titel :
Computer Application and System Modeling (ICCASM), 2010 International Conference on
Conference_Location :
Taiyuan
Print_ISBN :
978-1-4244-7235-2
Electronic_ISBN :
978-1-4244-7237-6
DOI :
10.1109/ICCASM.2010.5620090