caomw / parallel-poisson-blending

The code implements Poisson Blending in parallel with CUDA and Cheetah to efficiently and automatically superimpose images without visible seams.

Parallelization of Poisson Blending

By Jason Ting, Ryan Lee, Alex Lehman

Final Project for Computer Science 205, Fall 2013 (Cris Cecka)

The objective of the Poisson Blending algorithm is to compose a source image and a target image in the gradient domain. The code implements Poisson Blending in parallel with CUDA and Cheetah to efficiently and automatically superimpose images without visible seams.

How to Run:

There are two ways to run the code:

1. Using the images included in the folder and the course software load, execute the following on the Resonance node:
   $ python parallel_poisson.py [# iterations]

2. Specifying the image that you would like to process, execute the following, again on the Resonance node:
   $ python parallel_poisson.py [source image] [destination image] [# iterations]

Benchmarking:

For the purposes of analysis, the average time per iteration was computed over 800 iterations (N) for destination images of 5 sizes: (200, 142), (375, 266), (750, 531), (1500, 1062), and (2500, 1770).