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Fast Image Segmentation Algorithm Based on Salient Features Model and Spatial-frequency Domain Adaptive Kernel 被引量:4
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作者 WU Fupei LIANG Jiaye LI Shengping 《Instrumentation》 2022年第2期33-46,共14页
A fast image segmentation algorithm based on salient features model and spatial-frequency domain adaptive kernel is proposed to solve the accurate discriminate objects problem of online visual detection in such scenes... A fast image segmentation algorithm based on salient features model and spatial-frequency domain adaptive kernel is proposed to solve the accurate discriminate objects problem of online visual detection in such scenes of variable sample morphological characteristics,low contrast and complex background texture.Firstly,by analyzing the spectral component distribution and spatial contour feature of the image,a salient feature model is established in spatial-frequency domain.Then,the salient object detection method based on Gaussian band-pass filter and the design criterion of adaptive convolution kernel are proposed to extract the salient contour feature of the target in spatial and frequency domain.Finally,the selection and growth rules of seed points are improved by integrating the gray level and contour features of the target,and the target is segmented by seeded region growing.Experiments have been performed on Berkeley Segmentation Data Set,as well as sample images of online detection,to verify the effectiveness of the algorithm.The experimental results show that the Jaccard Similarity Coefficient of the segmentation is more than 90%,which indicates that the proposed algorithm can availably extract the target feature information,suppress the background texture and resist noise interference.Besides,the Hausdorff Distance of the segmentation is less than 10,which infers that the proposed algorithm obtains a high evaluation on the target contour preservation.The experimental results also show that the proposed algorithm significantly improves the operation efficiency while obtaining comparable segmentation performance over other algorithms. 展开更多
关键词 Image Segmentation spatial-frequency Domain Adaptive Convolution Kernel Online Visual Detection
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Joint spatial-frequency blind multiuser detection based on LCCMA 被引量:2
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作者 ZHAO Fa-yong FENG Guang-zeng 《The Journal of China Universities of Posts and Telecommunications》 EI CSCD 2007年第2期19-22,共4页
Multicarrier code division multiple access (MC-CDMA) has the ability to combat with frequency selective fading and antenna array can enhance the performance of system. The paper proposes a novel joint spatial-freque... Multicarrier code division multiple access (MC-CDMA) has the ability to combat with frequency selective fading and antenna array can enhance the performance of system. The paper proposes a novel joint spatial-frequency blind multiuser detection for antenna array MC-CDMA based on linear constraint constant modulation algorithm (LCCMA), which has robust performance and can ensue the weight vectors to converge to that of the desired user Simulation indicates the proposed algorithm has better bit error ratio (BER) performance than that of the traditional beamforming-based two-step algorithm. 展开更多
关键词 antenna array MC-CDMA LCCMA joint spatial-frequency blind multiuser detection
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