Comparison to
Lai et al. 2009


We compare against method described in

Yu-Kun Lai and Shi-Min Hi and Ralph R. Martin,
Automatic and Topology-Preserving Gradient Mesh Generation for Image Vectorization,
ACM Transactions on Graphics 23(3), 2009

We used the author's implementation to create these results.

Please note: most vectorization tools, such as the algorithm described in the Lai et al.'s paper, are designed for much larger input images. In the paper we give a detailed explanation for why they perform less successfully on tiny pixel art inputs. The results below do not make a statement about the quality one can achieve on input images within the design range of these tools, they merely show that there is a need for specialized algorithms for very tiny images. It should also be noted that our algorithm does not generalize to large images with noise or anti-aliased edges. Please see Lai et al's paper to see some very nice results on such challenging images.


Boo
Super Mario World, © Nintendo

Input Nearest (16x) Our Method (16x) Lai et al., 2009


Mario and Yoshi 2
Super Mario World, © Nintendo

Input Nearest (8x) Our Method (8x) Lai et al., 2009


Bomber 4
Super Bomberman, © Hudson Soft

Input Nearest (16x) Our Method (16x) Lai et al., 2009


Yoshi 3
Super Mario World, © Nintendo

Input Nearest (16x) Our Method (16x) Lai et al., 2009