A new intensity-hue-saturation fusion approach to image fusion with a tradeoff parameter

A useful technique in various applications of remote sensing involves the fusion of panchromatic and multispectral satellite images. Recently, Tu et al. introduced a fast intensity-hue-saturation (IHS) fusion method. Aside from its fast computing capability for fusing images, this method can extend traditional three-order transformations to an arbitrary order. It can also quickly merge massive volumes of data by requiring only resampled multispectral data. However, fast IHS fusion also distorts color in the same way as fusion processes such as the IHS fusion technique. To overcome this problem, the minimization problem for a fast IHS method was considered and the method proposed by Gonza/spl acute/lez-Aud/spl inodot//spl acute/cana et al. is presented as a solution. However, the method is not efficient enough to quickly merge massive volumes of data from satellite images. The author therefore uses a tradeoff parameter in a new approach to image fusion based on fast IHS fusion. This approach enables fast, easy implementation. Furthermore, the tradeoff between the spatial and spectral resolution of the image to be fused can be easily controlled with the aid of the tradeoff parameter. Therefore, with an appropriate tradeoff parameter, the new approach provides a satisfactory result, both visually and quantitatively.

[1]  Te-Ming Tu,et al.  A new look at IHS-like image fusion methods , 2001, Inf. Fusion.

[2]  Amrane Houacine,et al.  Redundant versus orthogonal wavelet decomposition for multisensor image fusion , 2003, Pattern Recognit..

[3]  J. G. Liu,et al.  Smoothing Filter-based Intensity Modulation : a spectral preserve image fusion technique for improving spatial details , 2001 .

[4]  J. Schott,et al.  Resolution enhancement of multispectral image data to improve classification accuracy , 1993 .

[5]  Y. Chibani,et al.  The joint use of IHS transform and redundant wavelet decomposition for fusing multispectral and panchromatic images , 2002 .

[6]  Andrea Garzelli,et al.  Context-driven fusion of high spatial and spectral resolution images based on oversampled multiresolution analysis , 2002, IEEE Trans. Geosci. Remote. Sens..

[7]  A. Bovik,et al.  A universal image quality index , 2002, IEEE Signal Processing Letters.

[8]  Te-Ming Tu,et al.  A fast intensity-hue-saturation fusion technique with spectral adjustment for IKONOS imagery , 2004, IEEE Geoscience and Remote Sensing Letters.

[9]  Christine Pohl,et al.  Multisensor image fusion in remote sensing: concepts, methods and applications , 1998 .

[10]  J. Zhou,et al.  A wavelet transform method to merge Landsat TM and SPOT panchromatic data , 1998 .

[11]  C. Eddie Moxey,et al.  Hypercomplex correlation techniques for vector images , 2003, IEEE Trans. Signal Process..

[12]  L. Wald,et al.  Fusion of satellite images of different spatial resolutions: Assessing the quality of resulting images , 1997 .

[13]  A. S. Solodovnikov,et al.  Hypercomplex Numbers: An Elementary Introduction to Algebras , 1989 .

[14]  J. G. Liu Evaluation of Landsat-7 ETM+ Panchromatic Band for Image Fusion with Multispectral Bands , 2000 .

[15]  Luciano Alparone,et al.  Image fusion—the ARSIS concept and some successful implementation schemes , 2003 .

[16]  P. Dutilleux An Implementation of the “algorithme à trous” to Compute the Wavelet Transform , 1989 .

[17]  Xavier Otazu,et al.  Multiresolution-based image fusion with additive wavelet decomposition , 1999, IEEE Trans. Geosci. Remote. Sens..

[18]  Myeong-Ryong Nam,et al.  Fusion of multispectral and panchromatic Satellite images using the curvelet transform , 2005, IEEE Geoscience and Remote Sensing Letters.

[19]  Yun Zhang,et al.  Understanding image fusion , 2004 .

[20]  L. Wald,et al.  Fusion of high spatial and spectral resolution images : The ARSIS concept and its implementation , 2000 .

[21]  Rafael García,et al.  Fusion of multispectral and panchromatic images using improved IHS and PCA mergers based on wavelet decomposition , 2004, IEEE Transactions on Geoscience and Remote Sensing.

[22]  Stephen J. Sangwine,et al.  Colour image filters based on hypercomplex convolution , 2000 .

[23]  Vassilis Tsagaris,et al.  Information measure for assessing pixel-level fusion methods , 2004, SPIE Remote Sensing.

[24]  Luciano Alparone,et al.  A global quality measurement of pan-sharpened multispectral imagery , 2004, IEEE Geoscience and Remote Sensing Letters.

[25]  W. Shi,et al.  Multi-band wavelet for fusing SPOT panchromatic and multispectral images , 2003 .