文件列表:

CVPR08-SR\coupled_dic_train.m (705, 2009-05-30)
CVPR08-SR\Data\Dictionary\Dictionary.mat (1766587, 2009-05-30)
CVPR08-SR\Data\Test\1.bmp (198198, 2007-11-25)
CVPR08-SR\Data\Test\2.bmp (169686, 2007-11-24)
CVPR08-SR\Data\Test\Thumbs.db (32768, 2009-05-30)
CVPR08-SR\Data\Training\t1.bmp (104246, 2007-10-14)
CVPR08-SR\Data\Training\t10.bmp (55266, 2007-10-14)
CVPR08-SR\Data\Training\t11.bmp (118614, 2007-10-14)
CVPR08-SR\Data\Training\t12.bmp (40990, 2007-10-14)
CVPR08-SR\Data\Training\t13.bmp (101010, 2007-10-14)
CVPR08-SR\Data\Training\t14.bmp (76990, 2007-10-14)
CVPR08-SR\Data\Training\t15.bmp (126618, 2007-10-14)
CVPR08-SR\Data\Training\t16.bmp (83894, 2007-10-14)
CVPR08-SR\Data\Training\t17.bmp (69786, 2007-10-14)
CVPR08-SR\Data\Training\t18.bmp (55782, 2007-10-14)
CVPR08-SR\Data\Training\t19.bmp (96174, 2007-10-14)
CVPR08-SR\Data\Training\t2.bmp (92418, 2007-10-14)
CVPR08-SR\Data\Training\t20.bmp (18462, 2007-10-14)
CVPR08-SR\Data\Training\t21.bmp (41346, 2007-10-14)
CVPR08-SR\Data\Training\t22.bmp (59718, 2007-10-14)
CVPR08-SR\Data\Training\t23.bmp (46902, 2007-10-14)
CVPR08-SR\Data\Training\t24.bmp (37290, 2007-10-14)
CVPR08-SR\Data\Training\t25.bmp (125190, 2007-10-14)
CVPR08-SR\Data\Training\t26.bmp (58742, 2007-10-14)
CVPR08-SR\Data\Training\t27.bmp (126030, 2007-10-14)
CVPR08-SR\Data\Training\t28.bmp (92550, 2007-10-14)
CVPR08-SR\Data\Training\t29.bmp (87526, 2007-10-14)
CVPR08-SR\Data\Training\t3.bmp (89334, 2007-10-14)
CVPR08-SR\Data\Training\t30.bmp (61662, 2007-10-14)
CVPR08-SR\Data\Training\t31.bmp (101670, 2007-11-09)
CVPR08-SR\Data\Training\t32.bmp (86646, 2007-11-09)
CVPR08-SR\Data\Training\t33.bmp (81706, 2007-11-09)
CVPR08-SR\Data\Training\t34.bmp (66362, 2007-11-09)
CVPR08-SR\Data\Training\t35.bmp (125306, 2007-11-09)
CVPR08-SR\Data\Training\t36.bmp (114102, 2007-11-22)
CVPR08-SR\Data\Training\t37.bmp (312390, 2007-11-22)
CVPR08-SR\Data\Training\t38.bmp (200054, 2007-11-22)
CVPR08-SR\Data\Training\t39.bmp (197350, 2007-11-22)
CVPR08-SR\Data\Training\t4.bmp (128646, 2007-10-14)
CVPR08-SR\Data\Training\t40.bmp (200082, 2007-11-22)
... ...

Description This package contains the Matlab codes implementing the super-resolution algorithm described in CVPR'08 paper "Image Super-resolution as Sparse Representation of Raw Image Patches". The codes vary a little from the original paper: a. The implementation is a simplified version of the algorithm described in the paper. The overlapping constraint for patches is not taken into sparse coding process. The backprojection process is not incorporated either. It seems that straight sparse coding itself can achieve similar performance. b. We trained the dictionary instead of random sampling in this version. A pre-trained dictionary is included (dictionary.mat). The algorithm is composed of the following parts: a. Dictionary training. We used Honglak Lee's package for learning the dictionary. We also include the training images we used in folder "Training". b. Sparse representation for super-resolution. Use sparse prior to infer the high resolution patch. Run Example.m to see how the functions are called. Have fun! For any questions, please email to jyang29@uiuc.edu

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