The two following labs deal with Poisson image editing, which can be used for image stitching, fusion, cloning, smoothing, context highlighting, color to gray conversion, and other applications.
The theory behind the labs can be found in the lectures:
Start by downloading the template of the assignment.
Use poisson.m
to check your solution.
1a: Implement a function that for a given image computes its gradients (calc_grad.m
) - 0.5 points
1b: Implement a function that computes a mask preferring gradients with greater magnitude (get_mask.m
) - 0.5 points
1c: Implement a function that merges two images according to a given mask (merge_image.m
) - 0.5 points
1d: Implement a function that merges two input gradient fields according to a given mask (merge_grad.m
) - 0.5 points
1e: Implement a function that computes divergence of a given gradient field (calc_div.m
) - 0.5 points
Compare your results to the reference:
2: Implement a function that solves Poisson equation by discretizing it into a system of linear equations which is solved iteratively using Gauss-Seidel method (solve_GS.m
) - 2.5 points
Compare your results to the reference:
3: Implement a function that solves Poisson equation by deconvolution in the frequency domain (solve_FT.m
) - 4 points
Compare your results to the reference:
4a: Do image cloning using images and mask in the data folder (mona_lisa.png
, ginevra_benci.png
, mona_mask.png
) - 0.5 points
mona_lisa.png
and ginevra_benci.png
using merge_image.m
function to see the discrepancy.
mona_lisa.png
and ginevra_benci.png
using calc_grad.m
.
merge_grad.m
and compute the divergence using calc_div.m
.
solve_GS.m
and solve_FT.m
.
4b: Do image fusion to simulate HDR photo using images in the data folder (car_low.png
and car_high.png
) - 0.5 points
car_low.png
and car_high.png
using calc_grad.m
.
get_mask.m
, merge the gradients using merge_grad.m
, and compute the divergence using calc_div.m
.
solve_FT.m
.
Compare your results to the reference:
calc_grad.m
get_mask.m
merge_image.m
merge_grad.m
calc_div.m
solve_GS.m
solve_FT.m
poisson.m
as well as your final output images generated in tasks 4a and 4b.
Keep the files in the root of the zip archive (zip directly the files, NOT a folder containing the files). The evaluation system searches for the files just in the root of zip archive.
The points will be assigned manually by TA after the deadline.