ID 原文 译文
58188 为了提高一致性模糊图像盲复原清晰度，针对复原过程中涉及的全变差模型先验约束问题，提出一种基于先验优化的一致性模糊盲复原算法. In order to improve the clarity of the blind restoration of the conformance fuzzy image，a priorfuzzy blind restoration algorithm based on the prior optimization is proposed for the study of the prior constraint problem of the full variational model involved in the restoration process.
58189 利用基于半高斯梯度算子的局部加权全变差模型提取模糊图像显著边缘，在去除噪声和纹理干扰的同时，可提高有利信息的保持能力; Firstly，the local weightedtotal variation model based on half Gauss gradient operator is used to extract the significant edge of theblurred image. The noise and texture interference are removed，and the ability to maintain the favorableinformation is improved.
58190 提出多尺度混合特性先验估计模糊核，增强了模糊核估计的准确性; Then a multi-scale mixed characteristic prior estimation of blur kernel is proposed to enhance the accuracy of blur kernel estimation.
58191 利用非盲去卷积得到了清晰的复原图像. Finally，clear restored images are obtained bynon-blind deconvolution.
58192 实验结果表明，相较其他算法，针对模拟模糊图像，所提算法的复原图像峰值信噪比平均提升约 1.7% ，结构相似性指数平均提升约 19.1% ; The experimental results show that compared with other algorithms，the proposed algorithm improves the average peak signal to noise ratio of the reconstructed image by about1. 7% ，and the average structure similarity index increases by about 19. 1% .
58193 针对真实模糊图像，复原图像伪影更少，边缘纹理细节更加清晰自然，整体视觉效果更好. In view of the real blurimage，the artifact of restored image is less，the edge texture details are more clear and natural，and theoverall visual effect is better.
58194 针对接收信号强度指示( ＲSSI) 测距定位精度和鲁棒性差的问题，提出了一种基于秩滤波和裴波那契树的信号强度定位( ＲF-ＲSSI-FTO) 算法. In order to solve the problem of poor ranging accuracy and robustness of received signalstrength indication ( ＲSSI) ，a signal strength localization algorithm based on rank filter and Fibonaccitree optimization ( ＲF-ＲSSI-FTO) was proposed.
58195 采用秩滤波方法对 ＲSSI 值进行去干扰滤波处理，可提高测距精度及鲁棒性; First，the rank filtering method was used to remove theinterference of the ＲSSI value to improve the accuracy and robustness of the ranging.
58196 引入裴波那契树优化算法对定位坐标进行全局和局部搜索寻优处理，可减小定位误差. Then，the Fibonacci tree optimization algorithm was introduced to optimize the global and local search of the positioning coordinates to reduce the positioning error.
58197 仿真结果表明，ＲF-ＲSSI-FTO算法能有效改善测距精度和鲁棒性，增强全局和局部搜索能力，提高定位精度. Simulation results show that the ＲF-ＲSSI-FTO algorithm can effectively improve ranging accuracy and robustness，enhance the global and local search ability，and improve positioning accuracy.