원문정보
보안공학연구지원센터(IJSEIA)
International Journal of Software Engineering and Its Applications
Vol.9 No.5
2015.05
pp.1-10
피인용수 : 0건 (자료제공 : 네이버학술정보)
초록
영어
We formulate model of kernel regression process which is exploited for image upsampling. The probabilistic process is studied for estimating missing information in an image. The term ‘linear regression’ is a designing tool for the relationship between a scalar dependent variable ‘b’ and one or more explanatory variables denoted ‘A.’ We provide some results of regression method that are tested on two natural images. Simulation results compare performance with various condition and parameter sets.
목차
Abstract
1. Introduction
2. Kernel Regression
3. Experimental Results
3.1. Performance Comparison on Various n for Regn
3.2. Performance Comparison with Upsampling Methods
4. Conclusion
References
1. Introduction
2. Kernel Regression
3. Experimental Results
3.1. Performance Comparison on Various n for Regn
3.2. Performance Comparison with Upsampling Methods
4. Conclusion
References
저자정보
참고문헌
자료제공 : 네이버학술정보