Directional Texture Transfer With Edge Enhancement
Author(s): Hochang Lee, Sanghyun Seo, Kyunghyun Yoon.
Article: Computers & Graphics, Vol. 35, No. 1, pp. 81--91,
2011.
[BibTeX] [DOI] 
Abstract:
Texture transfer re-renders a target image with high-frequency information (texture) taken from parts of a reference image that is matched locally to the target image using characteristics such as color. In this paper, we add a directional factor based on the flow of the target image, creating a stroke-like effect that follows edges more accurately. In addition, we propose a method to clearly express object boundaries by
considering the effect of the medium on edges in the reference image. We also show how to select an appropriate weight for this directional factor from the reference image.We demonstrate the suitability of this improved form of texture transfer for expressing various artistic styles, and compare our results with those from previous texture-transfer algorithms. We find that our algorithm can be adapted to texture synthesis as well.
GPU-based SoftAssign for Maximizing Image Utilization in Photomosaics
Marcos Slomp, Michihiro Mikamo, Bisser Raytchev, Toru Tamaki, Kazufumi Kaneda.
International Journal of Networking and Computing, Vol. 1, No. 2, pp. 211--229, July,
2011. [BibTeX]
Image and Video Abstraction by Coherence-Enhancing Filtering
Jan Eric Kyprianidis, Henry Kang.
Computer Graphics Forum, Vol. 30, No. 2, pp. 593--602,
2011. [BibTeX]
Real-Time Shape Illustration Using Laplacian Lines
Long Zhang, Ying He, Jiazhi Xia, Xuexiang Xie, Wei Chen.
IEEE Transactions on Visualization and Computer Graphics, Vol. 17, No. 7, pp. 993--1006, july,
2011. [BibTeX]