Binary operator design by k-nearest neighbor learning with application to image resolution increasing

International Journal of Imaging Systems and Technology

Volumn 11, Issue 5, 2000, Pages 331-339

  Kim, Hae Yong ^a  

^a UNIVERSITY OF SÃO PAULO   (Brazil)

Author keywords

[No Author keywords available]

Indexed keywords

LEARNING SYSTEMS; REAL TIME SYSTEMS; STATISTICAL METHODS;

IMAGE RESOLUTION;

COLOR IMAGE PROCESSING;

EID: 0034427159     PISSN: 08999457     EISSN: None     Source Type: Journal    
DOI: 10.1002/ima.1017     Document Type: Article

References (14)

1. Optimal mean-square N-observation digital morphological filters: I. Optimal binary filters
2. Decision theoretic generalizations of the PAC model for neural net and other learning applications
3. Morphological filtering as template matching
4. Quick construction of efficient morphological operators by computational learning
5. Automatic design of nonlinear filters by nearest neighbor learning
6. Segmentation-free printed character recognition by relaxed nearest neighbor learning of windowed operator
7. Fast binary image resolution increasing by k-nearest neighbor learning
8. Logically efficient spatial resolution conversion using paired increasing operators
9. Fast binary image processing using binary decision diagrams