3D Image Interpolation Based on Directional Coherence
Yongmei Wang
Department of Information Engineering
The Chinese University of Hong Kong
Zhunping Zhang
Computer Science and Technology
Tsinghua University
Baining Guo
Internet Graphics Group
Microsoft Research Asia
IEEE Workshop on Mathematical Methods in Biomedical Image Analysis,
pages 195-202, December 2001
Abstract
Image interpolation is of great importance in biomedical visualization
and analysis. In this paper, we present a novel gray-level interpolation
method called Directional Coherence Interpolation (DCI). The principal
advantage of the proposed approach is that it leads to significantly
higher visual quality in 3D rendering when compared with traditional
image interpolation methods. The basis of DCI is a form of directional
image-space coherence. DCI interpolates the missing image data along
the maximum coherence directions (MCD), which are estimated from the
local image intensity yet constrained by a generic smoothness term.
Since the edges of the image and the contents of the objects are well
preserved along the MCDs, DCI can incorporate image shape and structure
information without the prior requirement of explicit representation
of object boundary / surface.
A number of experiments were performed on both synthetic and real medical
images to evaluate the proposed approach. The experimental results show
that in addition to the substantial improvement of visual effects
(qualitative evaluation), the quantitative error measures of DCI are
also better than the conventional gray level linear interpolation.
Comparing with the shape-based interpolation scheme applied on gray-level
images, DCI has much lower computation cost.
back to Home page