張滿 顏普

摘要：該文提出了一種基于圖割和支持向量機(SVM)的彩色遙感圖像分割算法，首先針對在RGB空間中很難有效區(qū)分顏色相似性的問題,通過選擇更加符合顏色視覺特性的HSI顏色空間進行圖像處理與分析，然后利用圖割算法定義一個能量函數(shù)來判斷圖像中像素是屬于圖像前景還是圖像背景，從而有選擇的提取前景種子節(jié)點與背景種子節(jié)點。最后以前景種子節(jié)點與背景種子節(jié)點為SVM算法的訓練集對遙感圖像進行訓練分類，完成圖像的分割。實驗表明此方法是一種有效的彩色遙感圖像分割方法。

關鍵詞：圖像分割；支持向量機；圖割圖論；HIS

中圖分類號：TP391文獻標識碼：A文章編號：1009-3044(2012)16-3958-04

A Color Remote Sensing Image Segmentation Algorithm Based on Graph Cut and Support Vector Machine

ZHANG Man，YAN Pu

（Key Lab Intelligent Computing & Signal Ministry of Education,Anhui University, Hefei 230039,China)

Abstract：A color remote sensing image segmentation algorithm based on graph cut and support vector machine is proposed in this paper. Firstly, because it is difficulty to evaluate the similarity of two colors from their distance in RGB color space, color image processing is im? plemented in Hue Saturation Intensity (HSI) space which reflects the features of human vision. Secondly, An energy function is defined by graph cut algorithm for determining the image pixels belongs to the image background image and the prospects,then prospects seed nodes and background seed nodes are used as training set of SVM.Finally, remote sensing image are classified using SVM. A color remote sensing image segmentation is completed. Experiments show the efficiency of the proposed algorithm on color remote sensing images.

Key words：Image Segmentation; Support Vector Machine (SVM); Graphic Theory and Graph Cut; HIS

在對圖像的研究和應用中，人們往往僅對圖像中的某些部分感興趣，這些部分常稱為目標或前景（其他部分稱為背景），它們一般對應圖像中特定的具有獨特性質的區(qū)域。圖像分割就是把圖像空間劃分成若干個具有某些一致性屬性的不重疊區(qū)域并提取出感興趣目標的技術和過程，而對圖像空間的劃分建立在區(qū)域的相似性和非連續(xù)性基礎上。相似性就是說同一區(qū)域中的像素特征是類似的；非連續(xù)性表明不同區(qū)域間像素的特征存在突變。

圖像分割是從圖像中分割出感興趣的區(qū)域。典型的圖像分割算法包括基于區(qū)域的算法[1-3]和基于輪廓的算法[4-6]，而基于圖論的圖像分割技術是近年來圖像分割領域的一個研究熱點[7-9]。遙感圖像具有數(shù)據(jù)量大、模糊性較強、紋理細節(jié)豐富等特點，這就決定了無論在分割效率還是分割效果上都對遙感圖像的分割提出了比自然景色圖像分割更高的要求。

該文提出了一種基于圖割和支持向量機(SVM)的彩色遙感圖像分割算法，首先選擇更加符合顏色視覺特性的HSI顏色空間進行圖像處理與分析，然后利用圖割算法定義一個能量函數(shù)來判斷圖像中像素是屬于圖像前景還是圖像背景，從而有選擇的提取前景種子節(jié)點與背景種子節(jié)點。最后用前景種子節(jié)點和背景種子節(jié)點作為訓練集，并對遙感圖像進行SVM訓練分類，之后進行必要的后期處理，最終完成圖像的分割。

該文提出了一種基于圖割和支持向量機的彩色遙感圖像分割算法，利用圖割算法來判斷圖像中像素是屬于圖像前景還是圖像背景，從而有選擇的提取前景種子節(jié)點與背景種子節(jié)點,以前景種子節(jié)點與背景種子節(jié)點為訓練集對遙感圖像利用SVM進行訓練分類，最終完成圖像的分割，不僅消除圖割中產生的邊界模糊現(xiàn)象，且極大的提高了圖論方法分割的速度。實驗證明了該文算法速度快精度準，是一種有效的遙感圖像分割方法。

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