Watershed-based maximum-homogeneity filtering

被引：10

作者：

Hansen, MW ^{[1
]}

Higgins, WE

机构：

[1] Sarnoff Corp, Princeton, NJ 08543 USA

[2] Penn State Univ, Dept Elect Engn, University Pk, PA 16802 USA

[3] Penn State Univ, Dept Comp Sci & Engn, University Pk, PA 16802 USA

[4] Penn State Univ, Bioengn Program, University Pk, PA 16802 USA

来源：

IEEE TRANSACTIONS ON IMAGE PROCESSING | 1999年 / 8卷 / 07期

基金：

美国国家卫生研究院;

关键词：

edge-preserving filters; image enhancement; nonlinear filters; watershed analysis;

D O I：

10.1109/83.772247

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

We introduce an image enhancement method referred to as the watershed-based maximum-homogeneity filter. This method first uses watershed analysis to subdivide the image into homogeneous pixel clusters called catchment basins. Next, using an adaptive, local, catchment-basin selection scheme, similar neighboring catchment basins are combined together to produce an enhanced image. Because the method starts with watershed analysis, it can preserve edge information and run with high computational efficiency. Illustrative results show that the method performs well relative to other popular nonlinear filters.

引用

页码：982 / 988

页数：7

共 19 条

[1] A COMPUTATIONAL APPROACH TO EDGE-DETECTION [J].