ID 原文 译文
14175 光在水下传播存在吸收和散射现象,导致水下图像颜色失真、对比度低。 The phenomenon of absorption and scattering exists in underwater propagation of light, which may lead to the color distortion and low contrast of the underwater images.
14176 为此,提出了一种基于暗通道先验和伽马变换的水下图像增强算法。 For this reason,an underwater image enhancement algorithm based on dark channel prior and Gamma transform is proposed.
14177 首先,在RGB空间利用暗通道先验估计水下图像透射率和大气光照值,加权处理后得到自适应补偿参数,进而对图像颜色校正。 First of all,the underwater image transmittance and atmospheric illumination are estimated by dark channel prior in RGB space,and the adaptive compensation parameters are obtained after weighted processing. Then,the image color is corrected.
14178 在此基础上,将增强后的RGB图像转化到HSV颜色空间,对V通道进行自适应伽马变换,提高图像的对比度。 On this basis,the enhanced RGB image is transformed into HSV color space,and adaptive Gamma transform is carried out to the V-channel,thus to improve the contrast of the image.
14179 最后,在公用水下图像增强数据集(RUIE)上进行实验,并与现有增强算法进行比较。 Finally, experiments are carried out on the public underwater image enhancement dataset of RUIE, and comparison is made with the existing enhancement algorithms.
14180 实验结果表明,所提算法显著提高了水下图像的视觉质量,优于其他相关算法。 The experimental results show that the proposed algorithm significantly improves the visual quality of underwater images and is better than the other algorithms
14181 路径规划是无人机任务目标的重要组成部分,针对粒子群(PSO)算法早期收敛速度快,后期易陷入局部最优的缺点,提出一种结合天牛须搜索(BAS)算法的改进粒子群算法,并将其应用于无人机三维空间路径规划。 Path planning is an important part of the objective of UAV task. Considering that the Particle Swarm Optimization(PSO) algorithm is fast in convergence in the early stage and easy to fall into local optimum in the later stage,an improved PSO combined with the Beetle Antennae Search algorithm is proposed, which is applied to three-dimensional path planning of UAVs.
14182 在改进的粒子群算法中,利用天牛个体的优势,在每次迭代中都有自己对环境空间的判断,使路径更加合理,搜索效率更高。 In the improved PSO algorithm,by using the advantage of the individual beetle,which has its own judgment on the environment space in each iteration,the path is more reasonable and the search efficiency is higher.
14183 仿真结果表明,与粒子群算法相比,使用改进的粒子群算法进行无人机三维路径规划效果更好、代价更小。 The simulation results show that: Compared with PSO,the three-dimensional path planning of UAV based on improved PSO is more effective with less cost.
14184 针对传统DS证据理论无法有效解决高冲突证据融合的问题,提出基于平均证据和焦元距离的高冲突证据融合方法。 The classical DS evidence theory cannot effectively conduct high-conflict evidence fusion. To solve the problem‚a high-conflict evidence fusion method based on average evidence and focal element distance is proposed.