為了能夠更好地把來自多傳感器的圖象信息綜合起來, 以提高對圖象信息的分析和提取能力, 在研究了小波包圖象分析法之后, 提出了一種基于小波包變換的圖象融合方法. 由于小波包變換能對圖象進行多層次分解,包括對小波變換沒有細分的高頻部分也能進行進一步的分解, 因此小波包分析能夠為圖象提供一種比小波多分辨分析更加精細的分析方法. 利用此融合算法將由多傳感器獲得的同一目標不同波段的遙感圖象和不同分辨率的遙
感圖象進行融合后得到的融合圖象, 能夠很好地將源圖象的細節融合在一起. 通過與該融合圖象進行主觀與客觀的評價比較, 證明該融合方法可以獲得更好的融合效果.
關鍵詞　圖象融合　小波包變換　遙感圖象　融合算法
Abstract　In o rder to merge info rmat ion from mult i2senso r adequately and to imp rove abilit ies of info rmat ion analysis and feature ext ract ion, w e study w avelet packet analysis on image data and give a fusion method in p ixel level by means of w avelet packet t ransfo rm in th is paper. W avelet packet t ransfo rm decompo ses an image into low frequency band and h igh frequency band in different level. Besides decompo sing low frequency band in a h igher
scale, it decompo ses h igh frequency band in h igher scale w h ich w avelet analysis does no t do. It offers a mo re p recise w ay fo r image analysis than w avelet mult i2reso lut ion analysis. Th rough merging images data of different w avebands from mult i2senso r to the same object and different reso lut ion images data by app lying image fusion method based on w avelet packet analysis, w e get fused p ictures. The method can fuse details of input images successfully, so that it disp lay info rmat ion of the each input image perfect ly. Comparing w ith o ther fused images and app raising them on w ay of object ive and subject ive perfo rmance, w e can draw the conclusion that using th is image fusion method can get mo re sat isfacto ry result than using o thers.
Kegwords　Image fusion, W avelet packet t ransfo rm, Remo te sensing image, Fusion algo rithm