Image super-resolution based on a novel edge sharpness prior

Edges are of significant importance in visual resolution perception. In this paper, we propose a novel image super-resolution method by enhancing the edges in the low resolution image. We first define a new edge sharpness feature: gradient profile sharpness (GPS), which considers both the absolute magnitude and the spatial scattering of edge gradient profile. Then we learn the relationship between GPSs in high resolution images and low resolution images, and we formulate a linear GPS transform to provide gradient prior for image reconstruction. Our GPS can represent edge sharpness perceptually well. And our super-resolution method can output harmonious and faithful images with better reconstruction quality.

[1]  Nariman Farvardin,et al.  A perceptually motivated three-component image model-Part I: description of the model , 1995, IEEE Trans. Image Process..

[2]  William T. Freeman,et al.  Example-Based Super-Resolution , 2002, IEEE Computer Graphics and Applications.

[3]  Harry Shum,et al.  Gradient Profile Prior and Its Applications in Image Super-Resolution and Enhancement , 2011, IEEE Transactions on Image Processing.

[4]  Stephen Lin,et al.  Super resolution using edge prior and single image detail synthesis , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[5]  Raanan Fattal,et al.  Image upsampling via imposed edge statistics , 2007, ACM Trans. Graph..

[6]  Chi-Keung Tang,et al.  Fast image/video upsampling , 2008, SIGGRAPH 2008.

[7]  Raanan Fattal,et al.  Image and video upscaling from local self-examples , 2011, TOGS.

[8]  Eero P. Simoncelli,et al.  Image quality assessment: from error visibility to structural similarity , 2004, IEEE Transactions on Image Processing.

[9]  Hans-Peter Seidel,et al.  Visually significant edges , 2010, TAP.