Polarization-Based Material Classification from Specular Reflection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Surface Reflection: Physical and Geometrical Perspectives
IEEE Transactions on Pattern Analysis and Machine Intelligence
Constraining Object Features Using a Polarization Reflectance Model
IEEE Transactions on Pattern Analysis and Machine Intelligence
Polarization Phase-Based Method For Material Classification In Computer Vision
International Journal of Computer Vision
CVPR '96 Proceedings of the 1996 Conference on Computer Vision and Pattern Recognition (CVPR '96)
Reflectance-Based Material Classification for Printed Circuit Boards
ICIAP '03 Proceedings of the 12th International Conference on Image Analysis and Processing
IEEE Transactions on Pattern Analysis and Machine Intelligence
Pixel- and region-based image fusion with complex wavelets
Information Fusion
Using genetic algorithms and neural networks for surface land minedetection
IEEE Transactions on Signal Processing
Recovery of surface orientation from diffuse polarization
IEEE Transactions on Image Processing
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When light is reflected from object surface, its spectral characteristics will be affected by the surface's elemental composition, and its polarimetric characteristics will be governed by the surface's roughness and conductance. Polarimetric and multispectral imaging can provide complementary discriminative information in applications such as object separation. However, few methods have been proposed to fuse the information provided by polarimetric and multispectral imagery for better object separation results. Considering that the metal and dielectric materials, and the manmade objects and natural background have different polarimetric and multispectral features, in this paper we propose a simple yet powerful method for object separation by using the polarimetric and spectral characteristics of specular and diffuse reflected light. A polarimetric imagery fusion algorithm is first proposed based on the degree of linear polarization modulation to distinguish different objects. Then the spectral and polarimetric information, which can be extracted from the specular and diffuse reflected light, is fused by using the HSI color space mapping for more robust object separation. Experiments on real outdoor and indoor images are performed to evaluate the efficiency of the proposed scheme.