OpenCV 4.10.0-dev
Open Source Computer Vision
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Detailed Description

the inpainting algorithm

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.
 

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 [267].

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