OpenCV  3.4.19
Open Source Computer Vision
Enumerations | Functions

Enumerations

enum  {
  cv::INPAINT_NS = 0,
  cv::INPAINT_TELEA = 1
}
 

Functions

void cv::inpaint (InputArray src, InputArray inpaintMask, OutputArray dst, double inpaintRadius, int flags)
 Restores the selected region in an image using the region neighborhood. More...
 

Detailed Description

the inpainting algorithm

Enumeration Type Documentation

◆ anonymous enum

anonymous enum

#include <opencv2/photo.hpp>

Enumerator
INPAINT_NS 
Python: cv.INPAINT_NS

Use Navier-Stokes based method.

INPAINT_TELEA 
Python: cv.INPAINT_TELEA

Use the algorithm proposed by Alexandru Telea [209].

Function Documentation

◆ inpaint()

void cv::inpaint ( InputArray  src,
InputArray  inpaintMask,
OutputArray  dst,
double  inpaintRadius,
int  flags 
)
Python:
cv.inpaint(src, inpaintMask, inpaintRadius, flags[, dst]) -> dst

#include <opencv2/photo.hpp>

Restores the selected region in an image using the region neighborhood.

Parameters
srcInput 8-bit, 16-bit unsigned or 32-bit float 1-channel or 8-bit 3-channel image.
inpaintMaskInpainting mask, 8-bit 1-channel image. Non-zero pixels indicate the area that needs to be inpainted.
dstOutput image with the same size and type as src .
inpaintRadiusRadius of a circular neighborhood of each point inpainted that is considered by the algorithm.
flagsInpainting method that could be cv::INPAINT_NS or cv::INPAINT_TELEA

The function reconstructs the selected image area from the pixel near the area boundary. The function may be used to remove dust and scratches from a scanned photo, or to remove undesirable objects from still images or video. See http://en.wikipedia.org/wiki/Inpainting for more details.

Note
  • An example using the inpainting technique can be found at opencv_source_code/samples/cpp/inpaint.cpp
  • (Python) An example using the inpainting technique can be found at opencv_source_code/samples/python/inpaint.py