and MNF trans-formation was essential for N-FINDR algorithm,also it could improve later anomaly weighted detectivity,and subspace anomaly detection enhancing the detectives had been widely proved.After MNF transformation,N-FINDR was directly applied to extract endmembers from the original image,then ...
Keywords:Imageprocessing;Spectralendmemberextraction;N-FINDRalgorithm;Improvedstoprule; Pretreatmentofthefeatures;SupportVectorMachine(SVM) 1 引言 随着图像处理技术的发展,高光谱图像由于其 丰富的波谱信息得到越来越广泛的应用。“端元”被 定义为数据中代表类别特征的理想化纯数据_1】o提取 ...
[1] Winter, Michael E. “N-FINDR: An Algorithm for Fast Autonomous Spectral End-Member Determination in Hyperspectral Data.”Proc. SPIE Imaging Spectrometry V3753, (October 1999): 266–75. https://doi.org/10.1117/12.366289. Version History ...
In this paper, we proposed the improved fast N-FINDR algorithm aiming to decrease the computation cost by providing a relative smaller search range, i.e. the candidate endmember set which was only a subset of the entire feature space. N-FINDR algorithm assumed that all the endmembers ...
N-finder algorithm (N-FINDR) is probably one of most popular and widely used algorithms used for endmember extraction. Three major obstacles need to be overcome in its practical implementation. One is that the number of endmembers must be known a priori. A second one is the use of random...
影像,以经过优化的N-FINDR算法进行线性混合像元分解提取冬小麦种植面积,各省的误差均控制在正负4%左 右。利用同期多时相的HJ-1星分类数据作为参考值,在试验区域选择14个均匀分布的样区验证混合像元分解结 果。结果显示6个样区的相对误差在10%以内,其余8个样区的误差基本在15%左右。该研究可为冬小麦种植面 积的...
I want to find nCr(n choose r, if you will) modulo a prime. The trouble is that all the numbers i.e. n, r and prime are large and are of the order of 10^9. One method I could come up with is computing each of the three factorials individually(using FFT and multipoint evaluati...
N=100+(−235∗59+222)∗133= Decimal Byte Ring: The numeric value determined using the given set of values is said to be the byte ring. The function value used isMODfor the ring. The bite ring determines the total number of byte being used. ...
The first stage is a modified form of conventional linear prediction which generates an error or residue sequence in such a way that exact reconstruction of the original data sequence can be accomplished with a simple recovery algorithm. The second stage is bi-level sequence coding. Even though ...
Fuzzy c-means clustering algorithm (FCM) is sensitive to noise and less effective when handling high dimensional data set. Given that particle swarm optimization algorithm (PSO) has strong global search capability and efficient performan... WS Jang,HI Kang,BH Lee - International Conference on Intel...