Package: DRIP 2.4

Yicheng Kang

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) <doi:10.1214/aos/1024691468>, Qiu, P. and Yandell, B. (1997) <doi:10.1080/10618600.1997.10474746>, Qiu, P. (2009) <doi:10.1007/s10463-007-0166-9>, Kang, Y. and Qiu, P. (2014) <doi:10.1080/00401706.2013.844732>, Qiu, P. and Kang, Y. (2015) <doi:10.5705/ss.2014.054>, Kang, Y., Mukherjee, P.S. and Qiu, P. (2018) <doi:10.1080/00401706.2017.1415975>, Kang, Y. (2020) <doi:10.1080/10618600.2019.1665536>.

Authors:Yicheng Kang [aut, cre], Peihua Qiu [aut, ctb]

DRIP_2.4.tar.gz
DRIP_2.4.tar.gz(r-4.7-arm64)DRIP_2.4.tar.gz(r-4.7-x86_64)DRIP_2.4.tar.gz(r-4.6-arm64)DRIP_2.4.tar.gz(r-4.6-x86_64)
manual.pdf |manual.html✨
card.svg |card.png
DRIP/json (API)

# Install 'DRIP' in R:
install.packages('DRIP', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/kangy10/drip/issues

Uses libs:
  • openblas– Optimized BLAS
Datasets:

On CRAN:

Conda:

openblas

3.78 score 30 scripts 669 downloads 4 mentions 17 exports 0 dependencies

Last updated from:1f78e7e3b5. Checks:5 OK, 1 FAIL. Indexed: no.

TargetResultTimeFilesSyslog
linux-devel-arm64OK192
linux-devel-x86_64OK178
source / vignettesOK212
linux-release-arm64OK199
linux-release-x86_64OK204
wasm-releaseFAIL86

Exports:cv.jpexdKQedgeModify1edgeModify2edgeParSelPilotjpexJPLLK_surfacerestore3Stagerestore3StageParSelroofDiffroofEdgeroofEdgeParSelstepDiffstepEdgestepEdgeParSelsurfaceClustersurfaceCluster_bandwidth

Dependencies:

Discontinuous Regression and Image Processing

Rendered fromDRIP-vignette.Rmdusingknitr::rmarkdownon May 23 2026.

Last update: 2026-01-15
Started: 2024-11-18

Readme and manuals

Help Manual

Help pageTopics
Brain Imagebrain
Image of Circlescircles
Bandwidth Selection and Noise Level Estimationcv.jpex
Performance Measure of Edge DetectordKQ
Type-1 Modification ProcedureedgeModify1
Type-2 Modification ProcedureedgeModify2
Pilot help for parameter selection in edge detectionedgeParSelPilot
Blind Image Deblurringjpex
Jump-Preserving Local Linear Kernel SmoothingJPLLK_surface
Image of a Kidkid
Image of Pepperspeppers
Plot Parameter Selection Results in JPEX Deblurringplot.JPEX_Parameters
Plot the Residual Image from a JPLLK Estimationplot.JPLLK_Parameters
Plot Parameter Selection Results in Surface Estimationplot.Surface_Cluster_Parameters
Plot Parameter Selection Results in 3-Stage Estimationplot.Three_Stage_Parameters
Print Parameter Selection Results in Edge Detectionprint.Edge_Parameters
Print Parameter Selection Results in JPEX Deblurringprint.JPEX_Parameters
Print Parameter Selection Results in JPLLK Estimationprint.JPLLK_Parameters
Print Parameter Selection Results in Surface Estimationprint.Surface_Cluster_Parameters
Print Parameter Selection Results in 3-Stage Estimationprint.Three_Stage_Parameters
Three-Stage Denoising and Deblurringrestore3Stage
Parameter Selection in Three-Stage Image Restorationrestore3StageParSel
Roof Edge Detection StatisticsroofDiff
Roof Edge DetectorroofEdge
Parameter Selection in Roof Edge DetectionroofEdgeParSel
Synthetic Aperture Radar Imagesar
Step Edge Detection StatisticsstepDiff
Step Edge DetectorstepEdge
Parameter Selection in Step Edge DetectionstepEdgeParSel
Stop Sign Imagestopsign
Summarize Parameter Selection Results in Edge Detectionsummary.Edge_Parameters
Summarize Parameter Selection Results in JPEX Deblurringsummary.JPEX_Parameters
Summarize Parameter Selection Results in JPLLK Estimationsummary.JPLLK_Parameters
Summarize Parameter Selection Results in Surface Estimationsummary.Surface_Cluster_Parameters
Summarize Parameter Selection Results in 3-Stage Estimationsummary.Three_Stage_Parameters
Jump-Preserving Surface Estimation Using Pixel ClusteringsurfaceCluster
Bandwidth Selection for Clustering-Based Surface EstimationsurfaceCluster_bandwidth