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2D_Spectrum
- Author: Xianju Wang Summary: 2 Dimensional Spectral Estimation MATLAB Release: R12 Descr iption: Estimating the power spectrum associated with a random process is desirable in many applications. This package includes four impor
ImageFusionMethods
- 奥斯纳布吕克大学教授的Spatial and Spectral Evaluation of Image Fusion Methods介绍！
QualityDLL
- 对于图像质量的一些评价方法，包括熵、惯性矩、边缘能量、谱函数-Image quality evaluation for a number of methods, including entropy, moment of inertia, edge energy, spectral function, etc.
Deblurring-Images
- 本书介绍了图像去模糊化的一些基本的知识，并且主要针对svd和spectral decomposition的去模糊算法进行了介绍，以及对于这些方法的一些提高计算速度的算法进行了详细是介绍-This ebook intruduces some basic knowledge of deblurring, especially the methods of SVD and Spectral Decomposition, and some fast algorithms for the two meth
fusion_and_evaluate
- 图像融合中pan图像和多光谱融合的四种方法（IHS PCA 小波 小波结合PCA）和融合效果的评价指标计算（信息熵、Q4等指标）-Image fusion of the pan and multi-spectral image with four methods (IHS PCA wavelet wavelet combined PCA) and fusion effect evaluation method
spectrum-estimation
- 功率谱估计是利用有限长的数据估计信号的功率谱，广泛应用于各个领域。功率谱估计主要分为经典谱估计与现代谱估计。常用的经典谱估计方法有周期图法，相关法，周期图的改进法，常用的现代谱估计方法有最大熵谱估计，AR模型，MA模型，ARMA模型。经典谱估计适用于长序列的信号，其主要缺陷是描述功率谱波动的数字特征方差性能差，频率分辨率低，现代谱估计适用于短序列的信号，旨在改善谱估计的分辨率，并将其应用于实际地震资料的谱分析。 -Power spectrum estimation is the use of
BSR_source
- Contour Detection and Hierarchical Image Segmentation (UC Berkeley) MATLAB/C++混编 Arbela?ez, P., Maire, M., Fowlkes, C., & Malik, J. (2011). Contour Detection and Hierarchical Image Segmentation. IEEE Transactions on Pattern Analysis and Machine
gpdux
- There are good reference value, The method of cumulative contribution rate Spectral methods of computational fluid dynamics flow of some of the overall stability of the phenomenon.
bksnh
- Suppressed carrier type differential phase modulation, allan FOG output error variance analysis, Spectral methods of computational fluid dynamics flow of some of the overall stability of the phenomenon.
PCA
- 高光谱遥感与传统的单波段、多光谱数据相比，波段量大量增加、波段宽度极大降低，对地面目标的光谱特性的测度更加细致，然而波段的增多必然导致数据量急剧增加、计算量增大、信息冗余增加以及统计参数的估计偏差增大。因此，对高光谱数据进行降维处理具有重要意义。一方面，降维能够使图像远离噪声，提高图像数据质量；另一方面，能够去除图像中的无价值波段，减少波段数，从而降低计算量，提高运算效率。主成分分析是常用的高光谱数据降维处理方法之一。(Compared with the single band, hypersp
rr532
- matlab development toolbox support vector machine, Complex modulation coherent pulse train signal, Spectral methods of computational fluid dynamics flow of some of the overall stability of the phenomenon.