基于面向对象分类约束的融合方法研究  

An Image Fusion Method Based on Object-Oriented Image Classification

作　　者：林文娟[1] 陈云浩[1] 王朝[2] 冯通[3] 

机构地区：[1]北京师范大学资源学院,北京100875 [2]航天量子数码科技有限公司,北京100037 [3]香港中文大学地理与资源管理系

出　　处：《光学学报》2006年第3期347-354,共8页Acta Optica Sinica

基　　金：国家自然科学基金(40201036);测绘遥感信息工程国家重点实验室开放基金(WKL(03)0102);资助环境与地理信息系统北京市重点试验室开放基金(2004GIS1-4)资助课题

摘　　要：像素级融合方法中常出现色彩突变或色彩失真现象。通过分类信息对融合进行约束可以部分消除目标地物边界的这些现象。然而传统的基于像素分类的影像融合方法由于分类中的“椒盐效应”,导致融合效果受到一定的影响和限制。采用面向对象分类约束的方法对该融合方法进行改进。首先采用面向对象分类方法进行影像分类,解决了基于像素分类中的“椒盐效应”问题;其次将分类结果作为影像融合的约束条件,利用色度饱和度明度(HSV)变换进行融合;最后将该方法的结果与多种融合方法的结果进行定量比较,发现该方法除在目视上取得很好的增强效果外,在信息熵、方差等指标上也取得了很好的效果。Image fusion at pixel level without precise registration always causes wrong colors and other problem. Classification-based fusion scheme can effectively eliminate the incorrect color at the edge of the objective. But the traditional per-pixel classification results in the well-known salt and pepper effect. The only way to smooth the image is to use filters, and it would impact on the result of fusion. A method consisted of a sequential application of segmentation, classification and fusion techniques is proposed. Firstly, the object-oriented classification was used. And it can eliminate the influence of salt and pepper effect. Subsequently, according to the restriction of the precise classification result, adjusting the multi-spectral image, then the fusion by using Hue-Saturation-Value （HSV） color transformation. Finally, this merging technique was compared to other merging methods. The quantitative comparison result showed that it was not only provided a better visual representation but also had higher value in the variance and entropy.

关 键 词：信息光学 基于分类约束的影像融合 面向对象影像分类 遥感图像分割 色度-饱和度-明度变换 

分 类 号：TP751[自动化与计算机技术—检测技术与自动化装置]