init - 初始化项目

doc/py_tutorials/py_photo/py_inpainting/py_inpainting.markdown

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+Image Inpainting {#tutorial_py_inpainting}
+================
+
+Goal
+----
+
+In this chapter,
+    -   We will learn how to remove small noises, strokes etc in old photographs by a method called
+        inpainting
+    -   We will see inpainting functionalities in OpenCV.
+
+Basics
+------
+
+Most of you will have some old degraded photos at your home with some black spots, some strokes etc
+on it. Have you ever thought of restoring it back? We can't simply erase them in a paint tool
+because it is will simply replace black structures with white structures which is of no use. In
+these cases, a technique called image inpainting is used. The basic idea is simple: Replace those
+bad marks with its neighbouring pixels so that it looks like the neighbourhood. Consider the image
+shown below (taken from [Wikipedia](http://en.wikipedia.org/wiki/Inpainting)):
+
+![image](images/inpaint_basics.jpg)
+
+Several algorithms were designed for this purpose and OpenCV provides two of them. Both can be
+accessed by the same function, **cv.inpaint()**
+
+First algorithm is based on the paper **"An Image Inpainting Technique Based on the Fast Marching
+Method"** by Alexandru Telea in 2004. It is based on Fast Marching Method. Consider a region in the
+image to be inpainted. Algorithm starts from the boundary of this region and goes inside the region
+gradually filling everything in the boundary first. It takes a small neighbourhood around the pixel
+on the neighbourhood to be inpainted. This pixel is replaced by normalized weighted sum of all the
+known pixels in the neighbourhood. Selection of the weights is an important matter. More weightage is
+given to those pixels lying near to the point, near to the normal of the boundary and those lying on
+the boundary contours. Once a pixel is inpainted, it moves to next nearest pixel using Fast Marching
+Method. FMM ensures those pixels near the known pixels are inpainted first, so that it just works
+like a manual heuristic operation. This algorithm is enabled by using the flag, cv.INPAINT_TELEA.
+
+Second algorithm is based on the paper **"Navier-Stokes, Fluid Dynamics, and Image and Video
+Inpainting"** by Bertalmio, Marcelo, Andrea L. Bertozzi, and Guillermo Sapiro in 2001. This
+algorithm is based on fluid dynamics and utilizes partial differential equations. Basic principle is
+heurisitic. It first travels along the edges from known regions to unknown regions (because edges
+are meant to be continuous). It continues isophotes (lines joining points with same intensity, just
+like contours joins points with same elevation) while matching gradient vectors at the boundary of
+the inpainting region. For this, some methods from fluid dynamics are used. Once they are obtained,
+color is filled to reduce minimum variance in that area. This algorithm is enabled by using the
+flag, cv.INPAINT_NS.
+
+Code
+----
+
+We need to create a mask of same size as that of input image, where non-zero pixels corresponds to
+the area which is to be inpainted. Everything else is simple. My image is degraded with some black
+strokes (I added manually). I created a corresponding strokes with Paint tool.
+@code{.py}
+import numpy as np
+import cv2 as cv
+
+img = cv.imread('messi_2.jpg')
+mask = cv.imread('mask2.png',0)
+
+dst = cv.inpaint(img,mask,3,cv.INPAINT_TELEA)
+
+cv.imshow('dst',dst)
+cv.waitKey(0)
+cv.destroyAllWindows()
+@endcode
+See the result below. First image shows degraded input. Second image is the mask. Third image is the
+result of first algorithm and last image is the result of second algorithm.
+
+![image](images/inpaint_result.jpg)
+
+Additional Resources
+--------------------
+
+-#  Bertalmio, Marcelo, Andrea L. Bertozzi, and Guillermo Sapiro. "Navier-stokes, fluid dynamics,
+    and image and video inpainting." In Computer Vision and Pattern Recognition, 2001. CVPR 2001.
+    Proceedings of the 2001 IEEE Computer Society Conference on, vol. 1, pp. I-355. IEEE, 2001.
+2.  Telea, Alexandru. "An image inpainting technique based on the fast marching method." Journal of
+    graphics tools 9.1 (2004): 23-34.
+
+Exercises
+---------
+
+-#  OpenCV comes with an interactive sample on inpainting, samples/python/inpaint.py, try it.
+2.  A few months ago, I watched a video on [Content-Aware
+    Fill](http://www.youtube.com/watch?v=ZtoUiplKa2A), an advanced inpainting technique used in
+    Adobe Photoshop. On further search, I was able to find that same technique is already there in
+    GIMP with different name, "Resynthesizer" (You need to install separate plugin). I am sure you
+    will enjoy the technique.