Performing gradient blending

The goal of Poisson image editing is to perform seamless (gradient) blending (cloning) of an object or a texture from a source image (captured by a mask image) with a target image. We want to create a photomontage by pasting an image region onto a new background using Poisson image editing. The idea is from the SIGGRAPH 2003 paper, Poisson Image Editing, by Perez et al., which shows that blending using the image gradients produces much more realistic results.

The gradient of the source and output images in the masked region will be the same after seamless cloning is done. Moreover, the intensity of the target image and the output image at the masked region boundary will be the same. The following diagram shows how a source image patch g is integrated seamlessly with a target image f^* (over the region Ω), with a new image patch f (over the region Ω) obtained as a solution with a Poisson solver:

In this recipe, we will demonstrate seamless cloning with OpenCV-Python.

Getting ready

We will use an image of the Statue of Liberty as a source and an image of the Victoria Memorial Hall as the destination image. Let's start by importing the libraries. Make sure that the major version of OpenCV-Python is at least 3:

import cv2
import numpy as np
print(cv2.__version__)
# 3.4.2

How to do it...

The steps for this recipe are as follows:

1. Read the source, destination, and mask images:

src = cv2.imread("images/liberty.png")
dst = cv2.imread("images/victoria.png")
src_mask = cv2.imread("images/cmask.png")
print(src.shape, dst.shape, src_mask.shape)
# (480, 698, 3) (576, 768, 3) (480, 698, 3)

2. Run seamless cloning to blend the masked source around a center in the destination image and save the output image:

center = (275,250)
output = cv2.seamlessClone(src, dst, src_mask, center, \
                           cv2.MIXED_CLONE)
cv2.imwrite("images/liberty_victoria.png", output)

How it works...

The following screenshot shows the input and mask images used for gradient blending:

The cv2.seamlessClone() function was used with the flags parameter value as cv2.MIXED_CLONE, which is a classic method. This function implements Poisson image editing, using a Poisson solver to solve a system of (Poisson) equations, by keeping the gradients only at the edge locations (as Dirichlet boundary conditions).

You will get an output image along the lines of the following if you run the preceding code snippets: