The phase error estimated by phase gradient autofocus(PGA) is not based on a finite order polynomial mode, so PGA has a good autofocus property for arbitrary order phase error and is fit for high resolution airborne S...The phase error estimated by phase gradient autofocus(PGA) is not based on a finite order polynomial mode, so PGA has a good autofocus property for arbitrary order phase error and is fit for high resolution airborne SAR. But PGA has two shortcomings: first, it has a worse estimation property for fast changing phase error; second, there exists a section of linear phase in the phase error estimated by this algorithm. This paper introduces the idea of rank one phase estimate (ROPE) autofocus technique, and improves PGA. The improved PGA(IPGA) can successfully overcome both these shortcomings of PGA.展开更多
This paper proposes an autofocus algorithm used for Synthetic Aperture Radar (SAR) images, called Adaptive Kurtosis Optimization Autofocus Algorithm (AKOAA). The AKOAA can reduce the differ-ence between initial value ...This paper proposes an autofocus algorithm used for Synthetic Aperture Radar (SAR) images, called Adaptive Kurtosis Optimization Autofocus Algorithm (AKOAA). The AKOAA can reduce the differ-ence between initial value and real value in focusing by adaptively adjusting the initial value, therefore effec-tively improve the local extremum problem in the Contrast Optimization Autofocus Algorithm (COAA) and speed up the convergence velocity. The principle and realization method of AKOAA are thoroughly investi-gated, and experimental results using real L-band SAR data show that the focus speed of AKOAA is nearly doubled compared with that of the COAA, and the image contrast of AKOAA is improved as well.展开更多
Autofocus method based on the analysis of image content information is investigated to reduce the alignment error resulting from mark positioning uncertainty due to defocus in microstructure layered fabrication proces...Autofocus method based on the analysis of image content information is investigated to reduce the alignment error resulting from mark positioning uncertainty due to defocus in microstructure layered fabrication process based on multilevel imprint lithography. The applicability of several autofocus functions to the alignment mark images is evaluated concerning their uniformity, sharpness near peak, reliability and measure computation efficiency and the most suitable one based on power spectrum in frequency domain (PSFD) is adopted. To solve the problem of too much computation amount needed in PSFD algorithm, the strategy of interested region detection and effective image reconstruction is proposed and the algorithm efficiency is improved. The test results show that the computation time is reduced from 0.316 s to 0.023 s under the same conditions while the other merits of the function are preserved, which indicates that the modified algorithm can meet the mark image autofocusing requirements in response time, accuracy and robustness. The alignment error due to defocus which is about 0.5 μm indicated by experimental results can be reduced or eliminated by the autofocusing implementation.展开更多
文摘The phase error estimated by phase gradient autofocus(PGA) is not based on a finite order polynomial mode, so PGA has a good autofocus property for arbitrary order phase error and is fit for high resolution airborne SAR. But PGA has two shortcomings: first, it has a worse estimation property for fast changing phase error; second, there exists a section of linear phase in the phase error estimated by this algorithm. This paper introduces the idea of rank one phase estimate (ROPE) autofocus technique, and improves PGA. The improved PGA(IPGA) can successfully overcome both these shortcomings of PGA.
文摘This paper proposes an autofocus algorithm used for Synthetic Aperture Radar (SAR) images, called Adaptive Kurtosis Optimization Autofocus Algorithm (AKOAA). The AKOAA can reduce the differ-ence between initial value and real value in focusing by adaptively adjusting the initial value, therefore effec-tively improve the local extremum problem in the Contrast Optimization Autofocus Algorithm (COAA) and speed up the convergence velocity. The principle and realization method of AKOAA are thoroughly investi-gated, and experimental results using real L-band SAR data show that the focus speed of AKOAA is nearly doubled compared with that of the COAA, and the image contrast of AKOAA is improved as well.
基金Supported by National Natural Science Foundation of China (No50305026)Open Foundation of Guangxi Key Lab for Manufacturing Systems and Advanced Manufacturing Technology (No07109008-025-K)
文摘Autofocus method based on the analysis of image content information is investigated to reduce the alignment error resulting from mark positioning uncertainty due to defocus in microstructure layered fabrication process based on multilevel imprint lithography. The applicability of several autofocus functions to the alignment mark images is evaluated concerning their uniformity, sharpness near peak, reliability and measure computation efficiency and the most suitable one based on power spectrum in frequency domain (PSFD) is adopted. To solve the problem of too much computation amount needed in PSFD algorithm, the strategy of interested region detection and effective image reconstruction is proposed and the algorithm efficiency is improved. The test results show that the computation time is reduced from 0.316 s to 0.023 s under the same conditions while the other merits of the function are preserved, which indicates that the modified algorithm can meet the mark image autofocusing requirements in response time, accuracy and robustness. The alignment error due to defocus which is about 0.5 μm indicated by experimental results can be reduced or eliminated by the autofocusing implementation.
