Super-resolution of single text image by sparse representation
Proceeding of the workshop on Document Analysis and Recognition
An image super-resolution scheme based on compressive sensing with PCA sparse representation
IWDW'12 Proceedings of the 11th international conference on Digital Forensics and Watermaking
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Image super-resolution (SR) reconstruction is one of the most popular research topics in image processing for decades. This paper presents a novel approach to deal with single image SR problem. We search a mapping between a pair of low-resolution and high-resolution image patch in gradient domain by learning a generic image database and the input image itself. Given low-resolution image, the high-resolution image is reconstructed using sparse representation in gradient domain and solving Poisson equation. Experiments demonstrate that the state-of-the-art results have been achieved compared to other SR methods in terms of both PSNR and visual perception.