ID 原文 译文
22955 最后将增强后的伪雾图反转，即得到增强后的低照度图像。 The enhanced pseudo fog image is reversed to obtain the enhanced low illumination image.
22956 实验结果表明，针对低照度下的图像，该算法可以有效地提升对比度和亮度，过增强现象得到改善； Extensive experimental results using natural low-lighting images indicate that the proposed method perform better than contemporary algorithms in terms of several metrics, including the intensity, the contrast.
22957 效果优于对比算法，且复杂度低。 The proposed algorithm can effectively suppress the wrong phenomenon caused by enhanced with low complexity.
22958 该文提出一种基于压缩感知(Compressive Sensing, CS)的恒虚警率(Constant False Alarm Rate, CFAR)目标检测算法，首先分析了目标在距离单元上具有稀疏特性，并构造了目标回波的稀疏字典，设计特定的测量矩阵以及基于 CS 的 CFAR 检测结构，然后实现了对回波信号的压缩测量和 CFAR 检测，无需对回波信号重构。 A new Constant False Alarm Rate (CFAR) target detection algorithm is proposed based on Compressive Sensing (CS). Firstly, the sparsity of target in the distance dimension is analyzed and the sparse dictionary is constructed for the echo signal. Secondly, a certain measurement matrix and CFAR detection structure are designed based on CS. The proposed detector can detect sparse signals directly with high accuracy without any signal reconstruction.
22959 该文提出的算法具有很好的降噪性能并提高了检测效率，可以对低信噪比、低信杂比信号成功检测。 The proposed algorithm has a good noise reduction performance, which can detect low SNR and low Signal-to-Interference Ratio (SIR) signals successfully.
22960 仿真结果表明：当信噪比为-14 dB，信杂比为-10 dB 时，该算法与传统匹配滤波检测算法相比，减少了一半数据运算量，性能明显优于压缩匹配滤波检测算法。 Finally, computer simulation results verify that when SNR is equal to -14 dB and SIR is equal to -10 dB, the proposed detector can reduce the half measurements via compared with classical Matched Filter (MF) algorithm. What's more, the performance of the proposed detector is better than CS MF algorithm.
22961 行人再识别就是在无重叠视域多摄像机监控系统中，识别出相同的行人。 Person re-identification is the identification of the same pedestrian in a multi camera surveillance without overlapping views.
22962 针对来自于不同摄像头行人图片存在着视角、光照和尺度变化的问题，该文提出了基于支持样本间接式匹配的行人再识别方法。 Aiming at the problem of the existence of visual angle, illumination and scale change in pedestrian images which from different camera. An indirect person re-identification method is proposed based on the support samples.
22963 该算法首先通过聚类的方法分别提取不同摄像头下的支持样本，当要对来自不同摄像头的行人进行匹配时，在距离测度的基础上利用支持样本分别判别出其所在摄像头下的行人类别，通过类别的对比判断是否为同一行人。 At first, the algorithm extracts the support samples from different cameras by the clustering method. When it comes to matching pedestrians from different cameras,  the support samples are used to distinguish the pedestrians categories under the camera on the basis of the distance metric, by comparing the categories to determine whether the same pedestrian.
22964 该方法避免了不同摄像头下行人图片直接匹配，有效解决不同摄像头带来的视角、光照和尺度问题。 The method avoids the direct matching of pedestrian images under different cameras, which effectively solve the problem of the existence of visual angle, illumination and scale change in different camera.