Title :
Watershed-based maximum-homogeneity filtering
Author :
Hansen, Michael W. ; Higgins, William E.
Author_Institution :
Sarnoff Corp., Princeton, NJ, USA
fDate :
7/1/1999 12:00:00 AM
Abstract :
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
Keywords :
image enhancement; image segmentation; nonlinear filters; adaptive local catchment-basin selection scheme; catchment basins; computational efficiency; edge information; enhanced image; homogeneous pixel clusters; image enhancement method; neighboring catchment basins; watershed analysis; watershed-based maximum-homogeneity filtering; Adaptive filters; Computational efficiency; Filtering; Image analysis; Image edge detection; Image enhancement; Image segmentation; Information analysis; Nonlinear filters; Pixel;
Journal_Title :
Image Processing, IEEE Transactions on