The schlieren interferograms used to be analyzed in a qualitative way. In this paper, by means of the powerful computational ability and the large memory of computer; the image processing method is investigated for th...The schlieren interferograms used to be analyzed in a qualitative way. In this paper, by means of the powerful computational ability and the large memory of computer; the image processing method is investigated for the digitalization of an axisymmetric schlieren interferogram and the determination of the density field. This method includes the 2-D low-pass filtering, the thinning of interferometric fringes, the extraction of physical information and the numerical integration of the density field. The image processing results show that the accuracy of the quantitative analysis of the schlieren interferogram can be improved and a lot of time can be saved in dealing with optical experimental results. Therefore, the algorithm used here is useful and efficient.展开更多
For the polarimetric synthetic aperture radar interferometry (PoIInSAR) processing, it is necessary to coregister all the images, including the coregistration of polarimetric SAR images and the coregistration of inter...For the polarimetric synthetic aperture radar interferometry (PoIInSAR) processing, it is necessary to coregister all the images, including the coregistration of polarimetric SAR images and the coregistration of interferometric SAR images. Otherwise, the performance of the estimated optimal interferograms will be deteriorated. A generalized scattering vector (GSV) model is proposed to execute the PoIInSAR optimal interferograms estimation. The generalized scattering vector is constructed by the Pauli scattering vectors of the processing pixel and the surrounding pixels. Even though there are coregistration errors, all the polarimetric information of the current processing pixel is entirely included in the generalized scattering vector. Therefore, the GSV-based method can automatically recover the optimal scattering mechanisms of the processing pixel with coregistration errors either in interferoemetric channels or polarimetric channels. Theoretical analysis and processing results of simulated PoISARPro data and real PALSAR data validate the effectiveness and correctness of the proposed method.展开更多
Interferogram noise reduction is a very important processing step in Interferometric Synthetic Aperture Radar(InSAR) technique. The most difficulty for this step is to remove the noises and preserve the fringes simult...Interferogram noise reduction is a very important processing step in Interferometric Synthetic Aperture Radar(InSAR) technique. The most difficulty for this step is to remove the noises and preserve the fringes simultaneously. To solve the dilemma, a new interferogram noise reduction algorithm based on the Maximum A Posteriori(MAP) estimate is introduced in this paper. The algorithm is solved under the Total Generalized Variation(TGV) minimization assumption, which exploits the phase characteristics up to the second order differentiation. The ideal noise-free phase consisting of piecewise smooth areas is involved in this assumption, which is coincident with the natural terrain. In order to overcome the phase wraparound effect, complex plane filter is utilized in this algorithm. The simulation and real data experiments show the algorithm can reduce the noises effectively and meanwhile preserve the interferogram fringes very well.展开更多
In order to mitigate speckle noise in synthetic aperture radar(SAR)images and enhance the accuracy of SAR tomography,non-local means(NL-means)filtering has been proven to be an effective method for improving the quali...In order to mitigate speckle noise in synthetic aperture radar(SAR)images and enhance the accuracy of SAR tomography,non-local means(NL-means)filtering has been proven to be an effective method for improving the quality of SAR interferograms.Apart from considerations like noise type and the definition of similarity,the size and shape of filtering windows are critical factors influencing the efficacy of NL-means filtering,yet there has been limited research on this aspect.This paper introduces an enhanced NL-means filtering method based on adaptive windows,allowing for the automatic adjustment of filtering window size according to the amplitude information of the SAR interferogram.Simultaneously,a directional window is incorporated to align SAR interferograms,achieving the dual objective of preserving filtering standards and retaining detailed information.Experimental results on interferogram filtering and tomography,based on TerraSAR-X data,demonstrate that the proposed method effectively reduces phase noise while maintaining texture accuracy,thereby improving tomography quality.展开更多
文摘The schlieren interferograms used to be analyzed in a qualitative way. In this paper, by means of the powerful computational ability and the large memory of computer; the image processing method is investigated for the digitalization of an axisymmetric schlieren interferogram and the determination of the density field. This method includes the 2-D low-pass filtering, the thinning of interferometric fringes, the extraction of physical information and the numerical integration of the density field. The image processing results show that the accuracy of the quantitative analysis of the schlieren interferogram can be improved and a lot of time can be saved in dealing with optical experimental results. Therefore, the algorithm used here is useful and efficient.
基金supported by the National Natural Science Foundation of China(6147127661671355)the Areospace T.T.&.C.Innovation Program
文摘For the polarimetric synthetic aperture radar interferometry (PoIInSAR) processing, it is necessary to coregister all the images, including the coregistration of polarimetric SAR images and the coregistration of interferometric SAR images. Otherwise, the performance of the estimated optimal interferograms will be deteriorated. A generalized scattering vector (GSV) model is proposed to execute the PoIInSAR optimal interferograms estimation. The generalized scattering vector is constructed by the Pauli scattering vectors of the processing pixel and the surrounding pixels. Even though there are coregistration errors, all the polarimetric information of the current processing pixel is entirely included in the generalized scattering vector. Therefore, the GSV-based method can automatically recover the optimal scattering mechanisms of the processing pixel with coregistration errors either in interferoemetric channels or polarimetric channels. Theoretical analysis and processing results of simulated PoISARPro data and real PALSAR data validate the effectiveness and correctness of the proposed method.
文摘Interferogram noise reduction is a very important processing step in Interferometric Synthetic Aperture Radar(InSAR) technique. The most difficulty for this step is to remove the noises and preserve the fringes simultaneously. To solve the dilemma, a new interferogram noise reduction algorithm based on the Maximum A Posteriori(MAP) estimate is introduced in this paper. The algorithm is solved under the Total Generalized Variation(TGV) minimization assumption, which exploits the phase characteristics up to the second order differentiation. The ideal noise-free phase consisting of piecewise smooth areas is involved in this assumption, which is coincident with the natural terrain. In order to overcome the phase wraparound effect, complex plane filter is utilized in this algorithm. The simulation and real data experiments show the algorithm can reduce the noises effectively and meanwhile preserve the interferogram fringes very well.
基金supported in part by the National Natural Science Foundation of China(Nos.62201051,62101039)in part by the Shandong Excellent Young Scientists Fund Program(Overseas)in part by the National Key Research and Development Program of China(No.SQ2022YFB3900055).
文摘In order to mitigate speckle noise in synthetic aperture radar(SAR)images and enhance the accuracy of SAR tomography,non-local means(NL-means)filtering has been proven to be an effective method for improving the quality of SAR interferograms.Apart from considerations like noise type and the definition of similarity,the size and shape of filtering windows are critical factors influencing the efficacy of NL-means filtering,yet there has been limited research on this aspect.This paper introduces an enhanced NL-means filtering method based on adaptive windows,allowing for the automatic adjustment of filtering window size according to the amplitude information of the SAR interferogram.Simultaneously,a directional window is incorporated to align SAR interferograms,achieving the dual objective of preserving filtering standards and retaining detailed information.Experimental results on interferogram filtering and tomography,based on TerraSAR-X data,demonstrate that the proposed method effectively reduces phase noise while maintaining texture accuracy,thereby improving tomography quality.
