Image reconstruction using Loop subdivision

Zhou, Hailing, Zheng, Jianmin and Li, Xin 2010, Image reconstruction using Loop subdivision, in APSIPA/ASC 2010 - Proceedings of the 2nd 2010 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, [The Conference], [Biopolis, Singapore], pp. 1-1.


Title Image reconstruction using Loop subdivision
Author(s) Zhou, Hailing
Zheng, Jianmin
Li, Xin
Conference name Asia-Pacific Signal and Information Processing Association. Summit and Conference (2nd : 2010 : Biopolis, Singapore)
Conference location Biopolis, Singapore
Conference dates 14-17 Dec. 2010
Title of proceedings APSIPA/ASC 2010 - Proceedings of the 2nd 2010 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference
Editor(s) [Unknown]
Publication date 2010
Conference series Asia-Pacific Signal and Information Processing Association Annual Summit and Conference
Start page 1
End page 1
Total pages 1
Publisher [The Conference]
Place of publication [Biopolis, Singapore]
Summary It is an ultimate objective to reconstruct an image with high quality using a compact representation, which is the basic step in image-manipulation fields. We propose an effective vectorization based approach to reconstruct an image using a triangular mesh associated with Loop subdivision scheme in the present paper. With an initial control mesh obtained by simplifying a dense mesh from a quality-preserved triangulation, we produce the final optimal control mesh by optimizing a mesh over topologies and colors to approximate the given image. The main advantages of the approach include: (1) the reconstruction of an image is not restricted to be aligned with image coordinate axes; (2) a high order continuous function is defined over a triangle instead of a bilinear interpolation; (3) it is a compact and vector-based representation easy to edit and transmit. Experimental results are presented to confirm the effectiveness of the method. Comparisons with the bi-cubic spline and the mesh simplification methods demonstrate the merits of our method in reconstruction quality and representation size.
Language eng
Field of Research 080103 Computer Graphics
080104 Computer Vision
080106 Image Processing
Socio Economic Objective 970108 Expanding Knowledge in the Information and Computing Sciences
HERDC Research category EN.1 Other conference paper
Persistent URL http://hdl.handle.net/10536/DRO/DU:30049242

Document type: Conference Paper
Collection: Centre for Intelligent Systems Research
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