Texture characterization and classification of polarized images based on multi-angle orthogonal difference.

The Local Binary Pattern (LBP) and its variants are capable of extracting image texture and have been successfully applied to classification. However, LBP has not been used to extract and describe the texture of polarized images, and simple LBP cannot characterize the polarized texture information from different polarizations of angles. In order to solve these problems, we propose a new multi-angle orthogonal difference polarization image texture descriptor (MODP_ITD) by analyzing the relationship between the difference of orthogonal difference polarization images from different angles and the pixel intensity distribution in the local neighborhood of images from different angles.

Multi-angle orthogonal differential polarization characteristics and application in polarization image fusion.

With the wide application of image fusion technology in target detection and other fields, the fusion of polarization images and other intensity images is becoming a research focus. Traditional polarization image fusion includes intensity, degree of linear polarization (DOLP), and angle of polarization (AOP). However, images of DOLP and AOP fusion cannot meet the requirements of outstanding positive characteristics.