Multispectral image fusion for improved RGB representation based on perceptual attributes

A pixel‐level fusion technique for RGB representation of multispectral images is proposed. The technique results in highly correlated RGB components, a fact which occurs in natural colour images and is strictly related to the colour perception attributes of the human eye. Accordingly, specific properties for the covariance matrix of the final RGB image are demanded. Mutual information is employed as an objective criterion for quality refinement. The method provides dimensionality reduction, while the resulting RGB colour image is perceptually of high quality. Comparisons with existing techniques are carried out using both subjective and objective measures.

[1]  George K. Matsopoulos,et al.  Application of Morphological Pyramids: Fusion of MR and CT Phantoms , 1995, J. Vis. Commun. Image Represent..

[2]  Yuriy S. Shmaliy,et al.  System fusion in passive sensing using a modified hopfield network , 2001, J. Frankl. Inst..

[3]  Vladimir Petrovic,et al.  Objective image fusion performance measure , 2000 .

[4]  S. Marshall,et al.  Multiresolution morphological fusion of MR and CT images of the human brain , 1995 .

[5]  Tiranee Achalakul,et al.  Real‐time multi‐spectral image fusion , 2001, Concurr. Comput. Pract. Exp..

[6]  Luca Bogoni,et al.  Pattern-selective color image fusion , 2001, Pattern Recognit..

[7]  P. Chavez,et al.  STATISTICAL METHOD FOR SELECTING LANDSAT MSS RATIOS , 1982 .

[8]  G. Qu,et al.  Information measure for performance of image fusion , 2002 .

[9]  P. Chavez Radiometric calibration of Landsat Thematic Mapper multispectral images , 1989 .

[10]  J. Scott Tyo,et al.  Principal-components-based display strategy for spectral imagery , 2003, IEEE Trans. Geosci. Remote. Sens..

[11]  Bhabatosh Chanda,et al.  Fusion of 2D grayscale images using multiscale morphology , 2001, Pattern Recognit..

[12]  Zheng Liu,et al.  Image fusion by using steerable pyramid , 2001, Pattern Recognit. Lett..

[13]  Fu-Chun Zheng,et al.  Image fusion based on median filters and SOFM neural networks: : a three-step scheme , 2001, Signal Process..

[14]  M. Rast,et al.  Comparative digital analysis of Seasat-SAR and Landsat-TM data for Iceland , 1991 .

[15]  Azriel Rosenfeld,et al.  Computer Vision , 1988, Adv. Comput..

[16]  Anil K. Jain,et al.  A Markov random field model for classification of multisource satellite imagery , 1996, IEEE Trans. Geosci. Remote. Sens..

[17]  Alexander Toet,et al.  Perceptual evaluation of different image fusion schemes , 2003 .

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