Optical and SAR Image Registration Based on the Phase Congruency Framework

Abstract

The improved phase congruency (PC) algorithms have been successfully applied to optical and synthetic aperture radar (SAR) image registration since they are insensitive to nonlinear radiometric and geometric differences. However, most of the algorithms are sensitive to large-scale differences and rotation differences between optical and SAR images. To tackle this, we propose a PC framework to register optical and SAR images. It is compatible with large-scale and rotation invariance. Firstly, a multi-scale Harris keypoint extraction method based on the maximum moment of PC (named PC-Harris) is proposed. The scale space is constructed by combining PC with the log-Gabor filter. Secondly, we propose a PC model to construct the feature descriptors. The orientation and amplitude responses are obtained based on the PC model. Meanwhile, the novel descriptor is constructed based on the polar coordinate system and thus can handle the scale and rotation differences between optical and SAR images. Finally, outliers are removed by the fast sample consensus (FSC). The experiments conducted on several optical and SAR images verify the effectiveness of the proposed framework.

Principle and Recent Development in Photonic Time-Stretch Imaging

“…In order to improve the sensitivity, 2D devices, such as charge-coupled devices (CCD) and complementary metal oxide semiconductors (CMOS), 1D devices, such as photomultiplier tubes (PMT), avalanche photodetector (APD), and infrared-coated photodetector (PD) [60,61] are applied to improve the sensitivity of the imaging system. In order to obtain more specific information on the imaging systems, more techniques such as fluorescence imaging with biomarkers [62][63][64], phase-contrast imaging with interferometric structure for transparent sample imaging [65,66], and polarization-sensitive imaging are employed [67].…”

“…Among the improvement of current imaging systems, improving temporal resolution attracts a large amount of attention and obtained fruitful achievement. The most sparking technique for improving temporal resolution for imaging systems is PTS [66][67][68][69][70][71][72][73][74]-a technique that encodes the spatial profile of sample imaging information into the temporal profile data for ultrafast imaging using the dispersive medium in both spatial and temporal domains based on the dispersive properties of broadband light. It was proposed and demonstrated by Goda et al in 2009 for the first time [59].…”