海域使用管理的若干问题探讨

文章对海域使用管理中遇到的若干问题进行探讨,包括海洋功能区划符合性判别、海域使用论证及用海确权、岸线认定、填海项目竣工海域使用验收等方面内容,以期为海域使用精细化管理提供参考依据。海洋公益性行业科研专项经费资助(200905004

基于双域和ILoG−CLAHE的矿井红外图像增强算法

针对矿井复杂作业环境导致的红外图像降质，现有红外图像增强算法在实现信噪比和对比度提升的同时易丢失场景细节信息或造成目标边缘模糊的问题，提出了一种基于双域分解耦合改进的高斯−拉普拉斯（ILoG）算子和对比度受限自适应直方图均衡化（CLAHE）（ILoG−CLAHE）的矿井红外图像增强算法。首先，利用双域分解模型将矿井红外图像分解为包含高频信息的细节子图和低频信息的基础子图；其次，利用CLAHE算法对基础子图的亮度、对比度和清晰度进行提升，用以突出监视场景的概貌特征，采用构造的ILoG算子对细节子图进行噪声抑制和边缘锐化，并消除梯度反转现象；然后，通过重构处理后的基础子图和细节子图得到了图像质量改善后的重构图像；最后，设计了一种灰度重分布的Gamma校正函数，对重构图像进行亮度调整，进而得到矿井红外增强图像。通过主观视觉和客观指标对算法进行了性能分析，结果表明：经基于双域和ILoG−CLAHE的矿井红外图像增强算法增强后的矿井红外图像，整体视觉效果和客观指标均得到了较大提升，综合增强性能和鲁棒性更好。相较于原矿井红外图像和6种对比算法（CLAHE算法、双边滤波器（BF）分解与基础子图的CLAHE增强（BF−CLAHE）算法、BF分解与Gamma变换（BF−Gamma）算法、引导滤波与Gamma变换（GF−Gamma）算法、自适应直方图均衡化（AHE）耦合拉普拉斯变换（AHE−LP）算法、基于反锐化掩膜（UM）的图层融合（LF−UM）算法），该算法的综合评价指标值分别提高了0.28，0.11，0.23，0.38，0.57，0.04，0.10，图像亮度、清晰度和对比度均得到了较大提升，并且实现了噪声抑制和边缘锐化，表明该算法适用于矿井复杂作业环境中红外图像的增强处理

Prediction of Energy Resolution in the JUNO Experiment

International audienceThis paper presents the energy resolution study in the JUNO experiment, incorporating the latest knowledge acquired during the detector construction phase. The determination of neutrino mass ordering in JUNO requires an exceptional energy resolution better than 3% at 1 MeV. To achieve this ambitious goal, significant efforts have been undertaken in the design and production of the key components of the JUNO detector. Various factors affecting the detection of inverse beta decay signals have an impact on the energy resolution, extending beyond the statistical fluctuations of the detected number of photons, such as the properties of liquid scintillator, performance of photomultiplier tubes, and the energy reconstruction algorithm. To account for these effects, a full JUNO simulation and reconstruction approach is employed. This enables the modeling of all relevant effects and the evaluation of associated inputs to accurately estimate the energy resolution. The study reveals an energy resolution of 2.95% at 1 MeV. Furthermore, the study assesses the contribution of major effects to the overall energy resolution budget. This analysis serves as a reference for interpreting future measurements of energy resolution during JUNO data taking. Moreover, it provides a guideline in comprehending the energy resolution characteristics of liquid scintillator-based detectors