DRIP
Discontinuous Regression and Image Processing
A collection of functions that perform jump regression
and image analysis such as denoising, deblurring and
jump detection. The implemented methods are based on
the following research: Qiu, P. (1998)
DRIP
DRIP is a collection of functions for edge detection, image denoising and image deblurring. Below we categorize the functions based on their purpose.
Function overview
Edge detection
| Function | Description |
|---|---|
stepDiff() |
Step edge detection statistics |
stepEdge() |
Step edge detection |
stepEdgeParSel() |
Step edge detection parameter selection |
roofDiff() |
Roof edge detection statistics |
roofEdge() |
Roof edge detection |
roofEdgeParSel() |
Roof edge detection parameter selection |
edgeModify1() |
Edge modification |
edgeModify2() |
Edge modification |
edgeParSelPilot() |
Edge detection parameter selection |
dKQ() |
Edge detection performance measure |
Image denoising
| Function | Description |
|---|---|
restore3Stage() |
Three-stage denoising |
restore3StageParSel() |
Three-stage denoising parameter selection |
JPLLK_surface() |
Gradient-based denoising |
surfaceCluster() |
Clustering-based denoising |
surfaceCluster_bandwidth() |
Clustering-based denoising parameter selection |
Image deblurring
| Function | Description |
|---|---|
jpex() |
JPEX deblurring |
cv.jpex() |
JPEX deblurring parameter selection |
Installation
You can install the CRAN version of DRIP with:
install.packages("DRIP")