Nonlinear Approach for Enhancement of Image Focus Volume in Shape From Focus

Mostly, shape-from-focus algorithms use local averaging using a fixed rectangle window to enhance the initial focus volume. In this linear filtering, the window size affects the accuracy of the depth map. A small window is unable to suppress the noise properly, whereas a large window oversmoothes th...

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Bibliographic Details
Published in:IEEE transactions on image processing 2012-05, Vol.21 (5), p.2866-2873
Main Authors: Mahmood, M. T., Tae-Sun Choi
Format: Article
Language:English
Subjects:
Algorithms
Anisotropic nonlinear diffusion filtering (ANDF)
Applied sciences
depth map
Detection, estimation, filtering, equalization, prediction
Diffusion
Exact sciences and technology
Filtering
Filtration
focus measure
Image Enhancement - methods
Image Interpretation, Computer-Assisted - methods
Image processing
Image sequences
Information, signal and communications theory
Maximum likelihood detection
Noise
Nonlinear Dynamics
Nonlinearity
Rectangles
Reproducibility of Results
Sensitivity and Specificity
Shape
shape from focus (SFF)
Signal and communications theory
Signal processing
Signal, noise
Smoothing methods
Telecommunications and information theory
Three dimensional
Three dimensional displays
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Summary:Mostly, shape-from-focus algorithms use local averaging using a fixed rectangle window to enhance the initial focus volume. In this linear filtering, the window size affects the accuracy of the depth map. A small window is unable to suppress the noise properly, whereas a large window oversmoothes the object shape. Moreover, the use of any window size smoothes focus values uniformly. Consequently, an erroneous depth map is obtained. In this paper, we suggest the use of iterative 3-D anisotropic nonlinear diffusion filtering (ANDF) to enhance the image focus volume. In contrast to linear filtering, ANDF utilizes the local structure of the focus values to suppress the noise while preserving edges. The proposed scheme is tested using image sequences of synthetic and real objects, and results have demonstrated its effectiveness.
ISSN:1057-7149
1941-0042
DOI:10.1109/TIP.2012.2186144