Example-based super-resolution

被引:1818
作者
Freeman, WT [1 ]
Jones, TR [1 ]
Pasztor, EC [1 ]
机构
[1] Mitsubishi Elect Res Labs, Cambridge, MA USA
关键词
D O I
10.1109/38.988747
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
To address the lack of resolution independence in most models, we developed a fast and simple one-pass, training-based super-resolution algorithm for creating plausible high-frequency details in zoomed images.
引用
收藏
页码:56 / 65
页数:10
相关论文
共 21 条
[1]  
[Anonymous], P 34 ANN C INF SCI S
[2]  
[Anonymous], FUNDAMENTALS ELECT I
[3]  
Baker S, 2000, PROC CVPR IEEE, P372, DOI 10.1109/CVPR.2000.854852
[4]  
Efros AA, 2001, COMP GRAPH, P341, DOI 10.1145/383259.383296
[5]  
Fekri F, 1998, INT CONF ACOUST SPEE, P2657, DOI 10.1109/ICASSP.1998.678069
[6]   WHAT IS THE GOAL OF SENSORY CODING [J].
FIELD, DJ .
NEURAL COMPUTATION, 1994, 6 (04) :559-601
[7]   Learning low-level vision [J].
Freeman, WT ;
Pasztor, EC ;
Carmichael, OT .
INTERNATIONAL JOURNAL OF COMPUTER VISION, 2000, 40 (01) :25-47
[8]  
Freeman WT, 1999, ADV NEUR IN, V11, P775
[9]   STOCHASTIC RELAXATION, GIBBS DISTRIBUTIONS, AND THE BAYESIAN RESTORATION OF IMAGES [J].
GEMAN, S ;
GEMAN, D .
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 1984, 6 (06) :721-741
[10]   Image analogies [J].
Hertzmann, A ;
Jacobs, CE ;
Oliver, N ;
Curless, B ;
Salesin, DH .
SIGGRAPH 2001 CONFERENCE PROCEEDINGS, 2001, :327-340