A high spectrum exception detection method purifying backgrounds based on the local density

• Main Authors: ZONG SHIQIANG, MA WENTING, XIONG ZHAOHUA, HU ZHEN, WANG HUIJUAN, XU YING, WU WEI, ZHANG GUILIN, LI XIAODONG, XU LIN, WANG XINPENG
• Format: Patent
• Language: Chinese; English
• Published: 10.04.2018
• Subjects: CALCULATING; COMPUTING; COUNTING; IMAGE DATA PROCESSING OR GENERATION, IN GENERAL; PHYSICS

The invention provides a high spectrum exception detection method purifying backgrounds based on the local density. The method comprises the steps of: firstly acquiring an initial background corresponding to a currently detected pixel by using a concentric double-layer window model; then calculating the local density of each pixel of the initial background; setting the maximum exception proportionand selecting the pixel corresponding to the minimum local density according to the proportion; dividing the background by using the maximum between-cluster variance method; detecting a high spectrumimage based on an LRXD exception detection method; setting a threshold value, marking pixels with the detection values greater than the threshold value as exceptional points. The method removes exceptional data in backgrounds by purifying the backgrounds, thereby facilitating analysis of differences in targets and backgrounds and effectively reducing the false alarm rate. 本发明公开了种基于局部密度纯化背景的高光谱异常检测方法，首先，利用同心双层窗模型获取当前被检测像元对