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基于小波包变换的遥感图象融合
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2009-07-17
刘伟
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为了能够更好地把来自多传感器的图象信息综合起来, 以提高对图象信息的分析和提取能力, 在研究了小波包图象分析法之后, 提出了一种基于小波包变换的图象融合方法. 由于小波包变换能对图象进行多层次分解,包括对小波变换没有细分的高频部分也能进行进一步的分解, 因此小波包分析能够为图象提供一种比小波多分辨分析更加精细的分析方法. 利用此融合算法将由多传感器获得的同一目标不同波段的遥感图象和不同分辨率的遥
感图象进行融合后得到的融合图象, 能够很好地将源图象的细节融合在一起. 通过与该融合图象进行主观与客观的评价比较, 证明该融合方法可以获得更好的融合效果.
关键词 图象融合 小波包变换 遥感图象 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
感图象进行融合后得到的融合图象, 能够很好地将源图象的细节融合在一起. 通过与该融合图象进行主观与客观的评价比较, 证明该融合方法可以获得更好的融合效果.
关键词 图象融合 小波包变换 遥感图象 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
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