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A Kernel Regression Method for Images

Gwanggil Jeon
2015 International Journal of Software Engineering and Its Applications  
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
more » ... n and parameter sets. . His research interests fall under the umbrella of image processing, particularly image compression, motion estimation, demosaicking, and image enhancement as well as computational intelligence such as fuzzy and rough sets theories. He was the recipient of the IEEE Chester
doi:10.14257/ijseia.2015.9.5.01 fatcat:kiruf5aisvf53gv4tt37wyldwe