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NSCT
- 基于边缘和局部能量的NSCT变换遥感图像融合-Edge and local energy NSCT based remote sensing image fusion
LGIF
- 这是“Active contours driven by local and global intensity fitting energy with application to brain MR image segmentation”（简称LGIF模型）的MATLAB源代码。LGIF模型是非常重要局部区域活动轮廓模型, 它结合了CV模型和LBF模型各自的优点。-This is the "Active contours driven by local and global inten
curvelet
- 利用curvelet波将不同聚焦图像进行分解，然后利用局部能量最大的方法将图像合成，得到清晰的图像、-Curvelet waves using different focus image decomposition, and then make use of local energy will be the largest image synthesis methods have been given clear images,
PowerMaxImageFusion
- 图像融合是图像处理的一个研究热点，这里提供一种方法即局部能量最大选取规则图像融合法-Image fusion is image processing of a research hot spot that is here to provide a way to select the rules of the local energy of the largest image fusion method
tuxiangronghe
- exercise1:为基于小波变化与局部能量的图像融合方法 exercise2:为基于自适应算法的图像融合算法 myfunction1~myfunction5:为性能指标评价函数-exercise1: wavelet-based change and the local energy method of image fusion exercise2: adaptive algorithm based on image fusion algorithm myfunction1 ~ myfu
IEC_62056-61
- IEC 62056 Local communication OBIS codes for utility meters
1
- 图像融合算法，exercise1:为基于小波变化与局部能量的图像融合方法 exercise2:为基于自适应算法的图像融合算法 myfunction1~myfunction5:为性能指标评价函数-Image fusion algorithm, exercise1: wavelet-based change and the local energy method of image fusion exercise2: adaptive algorithm based on image fusi
imageronghe
- 图像融合算法，exercise1:为基于小波变化与局部能量的图像融合方法 exercise2:为基于自适应算法的图像融合算法 myfunction1~myfunction5:为性能指标评价函数-Image fusion algorithm, exercise1: wavelet-based change and the local energy method of image fusion exercise2: adaptive algorithm based on image fusi
LIF
- 一个新的主动轮廓模型算法，简化了传统的实现过程，性能也有所提高。相关论文(Active Contours Driven by Local Image Fitting Energy)发表在Pattern Recognition 2009上。-A new active contour model algorithm, simplifying the traditional implementation process, performance also improved. Related Paper
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- 认知无线电技术的提出是为提高频谱利用率，而认知无线实现的关键技术是频谱感知，众所周知协作检测提高了衰落环境中认知用户系统检测的性能，该文章是基于协作检测提出新的检测方案，利用了双门限方法提高了系统性能，兼顾带宽有限和增强性能两个方面，是基于门限检测的协作检测性能优化的前提。对以后门限优化协作检测非常有用。-In this paper, we employ a double threshold method in energy detector to perform spectrum sensin
waveletfilter
- 医学图像融合为临床诊断、手术设计与效果评估等提供不同模态影像互补信息。构造具有3 阶消失矩的双正交多小波滤 波器, 其以高斯函数一次泰勒规范展开正交化后得到的完备二次单位正交基作为尺度函数。利用构造的多小波滤波器, 分别对 CT、MRI 医学图像进行分解, 使用基于多小波分解改进的局部能量加权规则融合图像。结果表明改进规则融合了源图像主要信息, 优于常用的融合规则。应用构造的多小波滤波器可有效地融合医学图像, 略优于DGHM多小波-Medical image fusion provi
ActivecontoursdrivenbylocalGaussiandistributionfi
- Active contours driven by local Gaussian distribution fitting energy
LBF
- 这是“Implicit Active Contours Driven by Local Binary Fitting Energy”（简称LBF模型）的MATLAB源代码。LBF模型是非常重要局部区域活动轮廓模型，它被广泛使用于各个领域，如MRI大脑图像分割，血管图像分割，图像偏差场纠正。-This is the "Implicit Active Contours Driven by Local Binary Fitting Energy" (referred to as the LBF mod
9527
- exercise1:为基于小波变化与局部能量的图像融合方法 exercise2:为基于自适应算法的图像融合算法 myfunction1~myfunction5:为性能指标评价函数-exercise1: To change and local energy based on wavelet image fusion method exercise2: adaptive algorithm based image fusion algorithm myfunction1 ~ myfuncti
jubunengliang
- 表面肌电信号的小波包局部能量分解柱状图，提取特征能量-Local energy of the surface EMG wavelet packet decomposition histogram feature extraction energy
odot
- 演示一维信号的ODOT 和 Oslash “运营商的行动。这些运营商之一分解和结合的方式，局部能量模型与功能的看法是一致的信号。 -Demonstrate one-dimensional signal ODOT ' and' Oslash operator' s action. Decomposition and combination of one of the operators, the local energy model and function view is
OJ1211010001486B9EbH
- 基于局部能量与模糊逻辑的红外偏振图像融合，该文与小波包，支持向量机等融合算法进行对比分析，说明该文算法的优势。-Infrared polarization image fusion based on local energy and fuzzy logic, this paper, wavelet packet, support vector machines and other fusion algorithm comparison analysis to illustrate the adv
wavelet-change-and-the-local-energy
- 图像融合是图像处理的重要一环，但图像融合目前未有通用的技术，此代码试采用小波变换和局部能量相结合的方法对图像进行融合，试图达到一个较好的图像信息保留和处理-Image fusion is an important part of image processing, but the image fusion is at present no common technology, this code sample using wavelet transform and the method of c
Efficient-energy-consumption-and-operation-manage
- Microgrid works as a local energy provider for domestic buildings to reduce energy expenses and gas emissions by utilising distributed energy resources (DERs). The rapid advances in computing and communication capabilities enable the concept smar