Image vectorization using  blue-noise sampling

Jiaojiao Zhao; Jie Feng; Bingfeng Zhou

doi:10.1117/12.2009412

21 March 2013 Image vectorization using blue-noise sampling

Jiaojiao Zhao, Jie Feng, Bingfeng Zhou

Proceedings Volume 8664, Imaging and Printing in a Web 2.0 World IV; 86640H (2013) https://doi.org/10.1117/12.2009412
Event: IS&T/SPIE Electronic Imaging, 2013, Burlingame, California, United States

Abstract

Current image vectorization techniques mainly deal with images with simple and plain colors. For full-color photographs, many difficulties still exist in object segmentation, feature line extraction, and color distribution reconstruction, etc. In this paper, we propose a high-efficiency image vectorization method based on importance sampling and triangulation. A set of blue-noise sampling points is first generated on the image plane by an improved error-diffusion sampling method. The point set well preserves the features in the image. Then after triangulation on this point set, color information can be recorded on the mesh vertices to form a vector image. After certain image editing, e.g. scaling or transforming, the whole image can be reconstructed by color interpolating inside each triangle. Experiments show that the method has high performing efficiency and abilities in feature-preserving. It will bring benefits to many applications, e.g. image compressing, editing, transmitting and resolution enhancement.

Citation Download Citation

Jiaojiao Zhao, Jie Feng, and Bingfeng Zhou "Image vectorization using blue-noise sampling", Proc. SPIE 8664, Imaging and Printing in a Web 2.0 World IV, 86640H (21 March 2013); https://doi.org/10.1117/12.2009412

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