| Autor: |
XU Guoming, YUAN Hongwu, XUE Mogen, WANG Feng |
| Předmět: |
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| Zdroj: |
Systems Engineering & Electronics; Nov2020, Vol. 42 Issue 11, p2450-2460, 11p |
| Abstrakt: |
The polarization image pseudo color fusion is of great significance to improve visual perception and object interpretation. Based on the low-rank and sparse prior of the spatially modulated full-polarization parameter matrix, a fusion method is proposed via Bayesian probability robust matrix factorization. Firstly, the polarization parameter matrix is constructed according to the polarization modulation and analytic algorithm, and the intensity image is synthesized at the same time. Secondly, the sparse and low-rank components of the parameter images are obtained via improved Bayesian robust matrix factorization (BRMF). The influence of background noise and brightness change is reduced via BRMF. Then, the saliency parameter image is obtained by using the Choquet fuzzy integral of variance, definition and entropy. The saliency parameter image is carried out together with the synthesized intensity image to enforce pixel level enhancement. Finally, the pseudo color fusion image is obtained by the processing of histogram normalization and IHS color mapping. The experiment is performed with simulation and measurement images of different materials and objects. The subjective visual results and objective evaluation verify the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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