Name
Title | ||
|---|---|---|
Color shift model-based image enhancement for digital multifocusing based on a multiple color-filter aperture camera |
Abstract | ||
|---|---|---|
In this paper, we present a novel image enhancement approach using a color shift model-based multiple color-filter aperture (MCA) camera for digital multifocusing. The proposed image enhancement algorithm consists of three steps; (i) cluster-based region-of-interest (ROI) estimation, (ii) image registration using phase correlation matching (PCM) and fusion, and (iii) image enhancement using spatially adaptive noise smoothing based on the alpha map. The image acquired by the MCA configuration contains color misalignment, which provides additional depth information of objects at different distances. This color misalignment can also provide additional information for blur estimation. The proposed cluster-based image segmentation method can effectively classify ROIs according to the distance from the camera. The segmented regions are aligned by using PCM, and they are fused to generate an in-focused image. For further enhancement of the color-registered image, we use spatially adaptive noise smoothing based on the alpha map. Experimental results show the proposed image enhancement method can significantly enhance the visual quality of the MCA output image, and can be fully or partially incorporated into multifocusing or extended depth of field (EDoF) systems in the form of the finite impulse response (FIR) filter structure. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1109/TCE.2010.5505934 | IEEE Trans. Consumer Electronics |
Keywords | Field | DocType |
color shift model-based image,digital multifocusing,phase correlation matching,proposed cluster-based image segmentation,novel image enhancement approach,proposed image enhancement algorithm,spatially adaptive noise smoothing,multiple color-filter aperture,multiple color-filter aperture camera,in-focused image,color-registered image,mca output image,proposed image enhancement method,cluster-based region-of-interest estimation,color misalignment,image registration,image enhancement,colored noise,phase correlation,image restoration,depth of field,finite impulse response,fir filters,finite impulse response filter,image fusion,optical filters,fir filter,clustering algorithms,apertures,region of interest,image segmentation | Aperture,Computer vision,Image fusion,Computer science,Image segmentation,Smoothing,Artificial intelligence,Image restoration,Image registration,Color image,Depth of field | Journal |
Volume | Issue | ISSN |
56 | 2 | 0098-3063 |
Citations | PageRank | References |
1 | 0.36 | 8 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| E. Lee | 1 | 1 | 0.36 |
| W. Kang | 2 | 1 | 0.36 |
| Suhwan Kim | 3 | 494 | 74.23 |
| J. Paik | 4 | 144 | 8.83 |