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Adaptive image enhancement algorithm based on fuzzy entropy and human visual characteristics 被引量:3
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作者 WANG Baoping MA Jianjun +3 位作者 HAN Zhaoxuan ZHANG Yan FANG Yang GE Yimeng 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2018年第5期1079-1088,共10页
To overcome the shortcomings of the Lee image enhancement algorithm and its improvement based on the logarithmic image processing(LIP) model, this paper proposes what we believe to be an effective image enhancement al... To overcome the shortcomings of the Lee image enhancement algorithm and its improvement based on the logarithmic image processing(LIP) model, this paper proposes what we believe to be an effective image enhancement algorithm. This algorithm introduces fuzzy entropy, makes full use of neighborhood information, fuzzy information and human visual characteristics.To enhance an image, this paper first carries out the reasonable fuzzy-3 partition of its histogram into the dark region, intermediate region and bright region. It then extracts the statistical characteristics of the three regions and adaptively selects the parameter αaccording to the statistical characteristics of the image’s gray-scale values. It also adds a useful nonlinear transform, thus increasing the ubiquity of the algorithm. Finally, the causes for the gray-scale value overcorrection that occurs in the traditional image enhancement algorithms are analyzed and their solutions are proposed.The simulation results show that our image enhancement algorithm can effectively suppress the noise of an image, enhance its contrast and visual effect, sharpen its edge and adjust its dynamic range. 展开更多
关键词 image enhancement fuzzy entropy fuzzy partition logarithmic image processing(LIP) model human visual characteristic statistical characteristic
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Near field 3-D imaging approach for joint high-resolution imaging and phase error correction 被引量:2
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作者 Yang Fang Baoping Wang +2 位作者 Chao Sun Zuxun Song Shuzhen Wang 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2017年第2期199-211,共13页
This paper combines compressed sensing (CS) imaging theory and range migration algorithm (RMA), and then proposes a near-field three-dimensional (3-D) imaging approach for joint high-resolution imaging and phase error... This paper combines compressed sensing (CS) imaging theory and range migration algorithm (RMA), and then proposes a near-field three-dimensional (3-D) imaging approach for joint high-resolution imaging and phase error correction. Firstly, a sparse measurement matrix construction method based on a logistic sequence is proposed, which conducts nonlinear transformation for the determined logistic sequence, making it obey uniform distribution, then conducts sign function mapping, and generates the pseudorandom sequence with Bernoulli distribution, thus leading to good signal recovery under down-sampling and easy availability for engineering realization. Secondly, in combination with the RMA imaging approach, the dictionary with all scene information and phase error correction is constructed for CS signal recovery and error correction. Finally, the non-quadratic solution model jointing imaging and phase error correction based on regularization is built, and it is solved by two steps - the separable surrogate functionals (SSF) iterative shrinkage algorithm is adopted to realize target scattering estimate; the iteration mode is adopted for the correction of the dictionary model, so as to achieve the goal of error correction and highly-focused imaging. The proposed approach proves to be effective through numerical simulation and real measurement in anechoic chamber. The results show that, the proposed approach can realize high-resolution imaging in the case of less data; the designed measurement matrix has better non-coherence and easy availability for engineering realization. The proposed approach can effectively correct the phase error, and achieve highly-focused target image. © 2017 Beijing Institute of Aerospace Information. 展开更多
关键词 Compressed sensing Error correction Image reconstruction Iterative methods Linear transformations Mathematical transformations Signal reconstruction Signal sampling
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Multi-dimensional scattering properties diagnosis system of scale aircraft model in an anechoic chamber 被引量:1
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作者 Chufeng Hu Zhou Zhou +1 位作者 Nanjing Li Kun Zhang 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2014年第4期588-595,共8页
Aiming at the concept of "diagnosis", a simple and effective broadband radar cross section (RCS) measurement system is constructed, and some multi-dimensional scattering properties diagnosis techniques are present... Aiming at the concept of "diagnosis", a simple and effective broadband radar cross section (RCS) measurement system is constructed, and some multi-dimensional scattering properties diagnosis techniques are presented based on the system. Firstly, a stepped-frequency signal is employed to achieve high range resolution, combining with a variety of signal processing tech- niques. Secondly, cross-range resolution is gained with a rotating table, and the high-resolution two-dimensional (2-D) imaging of the scale model is obtained by the microwave imaging theory. Finally, two receiving antennas with a small distance in altitude are used, and the three-dimensional (3-D) height distribution of scattering points on the scale model is extracted from the phase of images. Some typical bodies and a scale aircraft model are diagnosed in an anechoic chamber. The experimental results show that, after scaling with a metal sphere, the accurate one- dimensional (l-D) RCS pattern of the model is obtained, and it has a large dynamic range. When the bandwidth of the transmitting signal is 4 GHz, the resolution of the 2-D image can reach to 0.037 5 m. The 3-D height distribution of scattering points is given by interferometric measurement. This paper provides a feasible way to obtain high-precision scattering properties parameters of the scale aircraft model in a conventional rectangular anechoic chamber. 展开更多
关键词 DIAGNOSIS STEPPED-FREQUENCY MULTI-DIMENSION anechoic chamber.
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