标题: An Iterative Joint Bilateral Filtering for Depth Refinement of a 3D Model [打印本页] 作者: 彬彬 时间: 2011-12-29 09:02 标题: An Iterative Joint Bilateral Filtering for Depth Refinement of a 3D Model 1 Introduction
Time-of-Flight (TOF) sensor is an acquisition device that can capture
the range data using an infrared pulse in real-time; however,
it is unsuitable to perform fine 3D scanning due to sensing limitations
such as low depth resolution and severe random noise. The
depth measurements between adjacent regions are not distinct so
that the reconstructed geometry often fails to express the details of
an original shape. To perform noise removal without a loss of details,
an edge-preserving filter by [Tomasi and Manduchi 1998]]
has been adopted. The joint bilateral filter [J. Kopf 2007] is also
used since it provides a better performance when additional information
such as a high resolution image is available. However, the
quality of acquired depth data needs more improvement to generate
a more precise 3D model. In this research, an iterative algorithm
is proposed based on the coarse-to-fine strategy to refine the depth
information acquired from TOF sensor. Our method focuses on the
reconstruction of 3D geometry from the measured depth map and
color images. Our method outperforms other filtering techniques in
noise reduction and the refinement of raw data.
2 Iterative joint bilateral filtering
The proposed algorithm refines the given depth map using two
steps. First, multi-scale images of an input depth map are generated
at user-specified levels using the Gaussian pyramid. It scales
down an image using the Gaussian kernel, which is equivalent to a
hierarchical low-pass filtering. In this step, a more reliable depth
distribution is obtained from the lowest scale depth map since the
