期刊文献+

基于IHS和小波变换的可见光与红外图像融合 被引量:10

Fusion of visual and infrared images based on IHS and wavelet transforms
下载PDF
导出
摘要 针对红外与可见光图像所表现的目标特征不同,提出了一种基于IHS和小波变换的图像融合方法.首先对可见光图像进行IHS变换得到亮度I、色度H、饱和度S 3个分量,再对红外图像进行灰度变换;然后对亮度分量和已变换红外图像进行小波分解,对低频分量和高频分量分别采用不同的融合规则;最后进行IHS逆变换得到融合图像.实验结果表明,该方法在红外与可见光图像融合处理中取得了很好的融合效果,优于传统的IHS变换法和小波变换方法.该方法保留了可见光图像高的空间分辨率和丰富的纹理细节信息,同时融合了在可见光图像中看不到而在红外图像里可以观察到的热目标. The infrared and visual images show different features for the same object,and considering these features this paper proposes an image fusion method based on IHS and wavelet transform.Firstly,the visual image is transformed by the IHS transform,and intensity(I),hue(H),saturation(S) components are obtained,and the infrared image is transformed by gray transform.Secondly,the intensity component and transformed infrared image are decomposed respectively by wavelet transform,different fusion rules are applied to coefficients of low frequency and high frequency.Finally,we could obtain the final fused image by IHS inverse transform.The experimental data shows the image fusion method is effective for the fusion of infrared and visual images and the fused image outperforms the traditional IHS transform method and the traditional IHS combining wavelet transform method.The proposed method can keep a high spatial resolution and rich texture detail information of visual image,and at the same time fuse the heat target that cannot be seen in the visible image while can be observed in the infrared image.
出处 《智能系统学报》 北大核心 2012年第6期554-559,共6页 CAAI Transactions on Intelligent Systems
基金 国家自然科学基金资助项目(61201238)
关键词 图像融合 小波变换 IHS变换 灰度变换 融合规则 image fusion wavelet transform IHS transform gray transform fusion rule
  • 相关文献

参考文献15

  • 1POHL C, Van GENDEREN J L. Muhisensor image fusion in remote sensing : concepts, methods and applications [ J ]. International Journal of Remote Sensing, 1998, 9 ( 5 ) : 823 -854.
  • 2蒋晓瑜.基于小波变换和伪彩色方法的多重图像融合算法研究[D].北京:北京理工大学光电工程系,1997.
  • 3胡江华,柏连发,张保民.象素级多传感器图像融合技术[J].南京理工大学学报,1996,20(5):453-456. 被引量:14
  • 4张加友,王江安.红外图像融合[J].光电子.激光,2000,11(5):537-539. 被引量:17
  • 5CARPER W J, LILLESAND T M, KIEFER R F. The use of intensity-hue-saturation transformations for merging SPOT panchromatic and multispeetral image data[ J ]. Photogram- metric Engineering & Remote Sensing, 1990, 56(4) : 459- 467.
  • 6Jr CHAVEZ P S, SIDES S C, ANDERSON J A. Compari- son of three difference methods to merge muhiresolution and multipectral data : landsat TM and SPOT panchromatic [ J ]. Photogrammetric Engineering & Remote Sensing, 1991, 57 (3) : 295-303.
  • 7BURT P J, ADELSON E H. The Laplacian pyramid as a compact image code [ J ]IEEE Trans Commun, 1983, 31 (4) : 532-540.
  • 8LAINE I K A, TAYLOR F. Image fusion using steerable dyadic wavelet transform[ C]//Proc of the IEEE Int'l Conf on Image Processing. Washington DC, USA, 1995: 232- 235.
  • 9DO M N, VETYERLI M. The contourlet transform: an ef- ficient directional multi-resolution image representation [J]. IEEE Transactions on Image Processing, 2005,14 (12) : 2091-2106.
  • 10吴怀群,黄宵宁,王建,杨忠,李桥梁.一种基于熵值的自动阈值图像分割方法[J].应用科技,2011,38(8):1-4. 被引量:5

二级参考文献39

  • 1玉振明,高飞.基于金字塔方法的图像融合原理及性能评价[J].计算机应用研究,2004,21(10):128-130. 被引量:38
  • 2孙红岩,毛士艺.多传感器目标识别的数据融合[J].电子学报,1995,23(10):188-193. 被引量:26
  • 3GONZALEZ R C, WOODS R E. Digital image processing [M]. 2nd ed. Beijing: Publishing House of Electronics Industry, 2001.
  • 4LEE S, CHUNG S, PARK R H. A comparative performance study of several global thresholding techniques for segmentation [ J ]. Computer Vision, Graphics, and Image Processing, 1990 (52): 171-190.
  • 5SAHOO P K, SOLTANI S, WONG A K C. A survey of thresholding technique [ J ] . Computer Vision graphics Image Process, 1988 (41) : 233-260.
  • 6OTSU N. A threshold selection method from gray-level histogram[J]. IEEE Trans on SMC-9, 1979-62-66.
  • 7PUN T. A new method for gray-level picture thresholding using the entropy of the histogram [J]. Signal Processing, 1980(2) : 223-237.
  • 8WHITWORTH C C, DULLER A W G, JONES D I, et al. Aerial video inspection of overhead power lines[J]. Power Engineering Journal, 2001, 2: 25-32.
  • 9KITTLER J, ILLINGWORTHV I. Minimum error thresholding [J]. Pattern Recognition, 1986, 19( 1 ) :4147.
  • 10CHO S, HARALICK R, YI S . Improvement of Kitder and Illingworth's minimum error thresholding [J]. Pattern Recognition, 1989, 22(5) : 609-617.

共引文献54

同被引文献102

引证文献10

二级引证文献17

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部