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Johannes Kopf     Dani Lischinski
Microsoft Research     The Hebrew University

Nearest-neighbor result (Original: 40 x 16 pixels) Our result

Naïve upsampling of pixel art images leads to unsatisfactory results. Our algorithm extracts a smooth, resolution-independent vector representation from the image which is suitable for high-resolution display devices (Image © Nintendo Co., Ltd.).


We describe a novel algorithm for extracting a resolution-independent vector representation from pixel art images, which enables magnifying the results by an arbitrary amount without image degradation. Our algorithm resolves pixel-scale features in the input and converts them into regions with smoothly varying shading that are crisply separated by piecewise-smooth contour curves. In the original image, pixels are represented on a square pixel lattice, where diagonal neighbors are only connected through a single point. This causes thin features to become visually disconnected under magnification by conventional means, and it causes connectedness and separation of diagonal neighbors to be ambiguous. The key to our algorithm is in resolving these ambiguities. This enables us to reshape the pixel cells so that neighboring pixels belonging to the same feature are connected through edges, thereby preserving the feature connectivity under magnification. We reduce pixel aliasing artifacts and improve smoothness by fitting spline curves to contours in the image and optimizing their control points.
    author  = {Johannes Kopf and Dani Lischinski},
    title   = {Depixelizing Pixel Art},
    journal = {ACM Transactions on Graphics (Proceedings of SIGGRAPH 2011)},
    year    = {2011},
    volume  = {30},
    number  = {4},
    pages   = {99:1 -- 99:8}
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