Long-wave infrared polarization feature extraction and image fusion based on the orthogonality difference method

Infrared polarization results from infrared-emitted radiation and reflected radiation effects. Polarization generated by infrared reflection is perpendicularly polarized, whereas polarization generated by infrared emission is parallelly polarized. Using the polarization feature in different directions can enhance the detection and discrimination of the target. Based on the Stokes vector, the polarization degree and angle are obtained. Then, according to the analysis of the polarization states, an orthogonality difference method of extracting polarization features is proposed. An infrared intensity and polarization feature images are fused using an algorithm of nonsubsampled shearlets transformation. Image evaluation indices of the target contrast to background (C), average gradient (AG), and image entropy (E) are employed to evaluate the fused image and original intensity image. Results demonstrate that every index of the fused image with the polarization feature is significantly improved, thereby validating the effectiveness of the proposed target-enhancement approach using polarization features extracted by the orthogonal difference method.