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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| Veröffentlicht in: | IEEE transactions on image processing 2012-05, Vol.21 (5), p.2866-2873 |
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| container_title | IEEE transactions on image processing |
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| creator | Mahmood, M. T. Tae-Sun Choi |
| description | 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. |
| doi_str_mv | 10.1109/TIP.2012.2186144 |
| format | Article |
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T.</creatorcontrib><creatorcontrib>Tae-Sun Choi</creatorcontrib><title>Nonlinear Approach for Enhancement of Image Focus Volume in Shape From Focus</title><title>IEEE transactions on image processing</title><addtitle>TIP</addtitle><addtitle>IEEE Trans Image Process</addtitle><description>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. 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T. ; Tae-Sun Choi</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c476t-ab1b02d01fe2887fadaa549c2c8c666ab33a3dcd7273d9c1eef4c164f6d2a39d3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2012</creationdate><topic>Algorithms</topic><topic>Anisotropic nonlinear diffusion filtering (ANDF)</topic><topic>Applied sciences</topic><topic>depth map</topic><topic>Detection, estimation, filtering, equalization, prediction</topic><topic>Diffusion</topic><topic>Exact sciences and technology</topic><topic>Filtering</topic><topic>Filtration</topic><topic>focus measure</topic><topic>Image Enhancement - methods</topic><topic>Image Interpretation, Computer-Assisted - methods</topic><topic>Image processing</topic><topic>Image sequences</topic><topic>Information, signal and communications theory</topic><topic>Maximum likelihood detection</topic><topic>Noise</topic><topic>Nonlinear Dynamics</topic><topic>Nonlinearity</topic><topic>Rectangles</topic><topic>Reproducibility of Results</topic><topic>Sensitivity and Specificity</topic><topic>Shape</topic><topic>shape from focus (SFF)</topic><topic>Signal and communications theory</topic><topic>Signal processing</topic><topic>Signal, noise</topic><topic>Smoothing methods</topic><topic>Telecommunications and information theory</topic><topic>Three dimensional</topic><topic>Three dimensional displays</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Mahmood, M. 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| 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 |
| title | Nonlinear Approach for Enhancement of Image Focus Volume in Shape From Focus |
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