Improved Super-Resolution method and its acceleration

A brief introduction to spatial-domain Super-Resolution methods, i.e. spatial resolution enhancement methods that create one high-resolution image from a series of low-resolution images shifted by a sub-pixel distance, is given. An improvement applicable to some of existing Super-Resolution methods is presented. Principles of digital photography processing techniques are exploited in order to reduce error in the Super-Resolution process. Enhanced registration method applicable to full color images is proposed and results of its hardware implementation are presented.

[1]  Takeo Kanade,et al.  Limits on super-resolution and how to break them , 2000, Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662).

[2]  Yuan Jian.  A Fast Super-resolution Reconstruction Algorithm , 2006 .

[3]  Russell C. Hardie,et al.  Joint MAP registration and high-resolution image estimation using a sequence of undersampled images , 1997, IEEE Trans. Image Process..

[4]  Michael Elad,et al.  Restoration of a single superresolution image from several blurred, noisy, and undersampled measured images , 1997, IEEE Trans. Image Process..

[5]  Wesley E. Snyder,et al.  Demosaicking methods for Bayer color arrays , 2002, J. Electronic Imaging.

[6]  Shmuel Peleg,et al.  Robust super-resolution , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.

[7]  Michael Elad,et al.  Fast and robust super-resolution , 2003, Proceedings 2003 International Conference on Image Processing (Cat. No.03CH37429).

[8]  Shmuel Peleg,et al.  Improving image resolution using subpixel motion , 1987, Pattern Recognit. Lett..

[9]  Roger Y. Tsai,et al.  Multiframe image restoration and registration , 1984 .

[10]  Michael Elad,et al.  A fast super-resolution reconstruction algorithm for pure translational motion and common space-invariant blur , 2001, IEEE Trans. Image Process..