G - glcm 中文 - EN166

glcm GLCM ＝ ground-launched cruis...

gleam
It first finds the best features that are extracted from glcm and explain the texture clearly in different resolution , and then segments on different level , at last , by combining the structure information of texture edge , extract the edge of different patterns to get a relatively accurate result of texture segmentation 該算法有效的利用了由灰度共現陣得到的、不同分辨率上最能表述紋理特性的統計特征,分層次對圖像進行分割,然后結合紋理的結構信息對邊緣區域進行邊界定位,進而得到較準確的紋理分割圖。
In this paper , we made an investigation into texture feature extraction and classification based on statistic method and its application in multi - spectral image classification . the research works of this paper have been done as follows : firstly , in order to overcome the weakness of gray level co - occurrence matrix ( glcm ) , a new unsupervised texture segment algorithm , based on multi - resolution model , is presented in this thesis 本文主要研究了基于紋理統計特性的特征提取與分割方法,并將其用于實際的多光譜圖像分類,具體工作如下:第一,針對傳統灰度共現陣方法中特征提取的尺度單一問題,本文提出了一種多分辨無監督紋理分割算法。
Among them the gray level co - occurrence matrix ( glcm ) and gray gradient co - occurrence matrix ( ggcm ) methods , which attributed to the statistic textural analysis scheme were then chosen to extract the textural features of five kind areas on satellite images . in the second part the principle of classification and bp neural network were introduced . combined with textural features , the improved bp neural network successfully performed on the classification of the satellite images 論文的第一部分介紹了進行紋理特征研究的一些典型的方法，利用其中的基于統計的紋理分析法中的灰度共生矩陣以及灰度一梯度共生矩陣法，分析了衛星云圖上五類區域的紋理特性；第二部分主要介紹了遙感圖像分類原理以及神經網絡中的bp算法，在對算法原理進行深入理解的基礎上，把紋理特征與神經網絡進行組合，實現對衛星云圖進行分類分析；第三部分內容是在前面圖像分類結果的基礎上，對序列圖像用相關匹配法進行運動分析，反演云跡風風場。
In order to realize the automation of wood classification and recognition , wood texture parameter system was constructed by glcm , and the research of classification was carried on 摘要為了實現木材分類識別的自動化，應用灰度共生矩陣建立了木材紋理的參數體系，并進行了分類研究。