Adaptive Image Enhancement Algorithm Combining Kernel Regression and Local Homogeneity
It is known that many image enhancement methods have a tradeoff between noise suppression and edge enhancement. In this paper, we propose a new technique for image enhancement filtering and explain it in human visual perception theory. It combines kernel regression and local homogeneity and evaluate...
Main Authors: | Yu-Qian Yang, Jiang-She Zhang, Xing-Fang Huang |
---|---|
Format: | Article |
Language: | English |
Published: |
Hindawi Limited
2010-01-01
|
Series: | Mathematical Problems in Engineering |
Online Access: | http://dx.doi.org/10.1155/2010/693532 |
Similar Items
-
Fast Image Search with Locality-Sensitive Hashing and Homogeneous Kernels Map
by: Jun-yi Li, et al.
Published: (2015-01-01) -
Joint-Saliency Structure Adaptive Kernel Regression with Adaptive-Scale Kernels for Deformable Registration of Challenging Images
by: Binjie Qin, et al.
Published: (2018-01-01) -
Image and Depth Image Upsampling Using Adaptive Local Weighted Kernel
by: Shi-Han Zhou, et al.
Published: (2015) -
Randomized Algorithms for Preconditioner Selection with Applications to Kernel Regression
by: DiPaolo, Conner
Published: (2019) -
An Efficient Kernel Learning Algorithm for Semisupervised Regression Problems
by: Chao Zhang, et al.
Published: (2015-01-01)