Discrete Cosine Transform based Image Fusion Techniques

Six different types of image fusion algorithms based on discrete cosine transform (DCT) were developed and their performance was evaluated. Fusion performance is not good while using the algorithms with block size less than 8x8 and also the block size equivalent to the image size itself. DCTe and DCTmx based image fusion algorithms performed well. These algorithms are very simple and might be suitable for real time applications.

[1]  Gonzalo R. Arce,et al.  Nonlinear Signal Processing - A Statistical Approach , 2004 .

[2]  N. Ahmed,et al.  Discrete Cosine Transform , 1996 .

[3]  Jinshan Tang,et al.  A contrast based image fusion technique in the DCT domain , 2004, Digit. Signal Process..

[4]  Henk J. A. M. Heijmans,et al.  A new quality metric for image fusion , 2003, Proceedings 2003 International Conference on Image Processing (Cat. No.03CH37429).

[5]  Gonzalo Pajares,et al.  A wavelet-based image fusion tutorial , 2004, Pattern Recognit..

[6]  Yaonan Wang,et al.  Combination of images with diverse focuses using the spatial frequency , 2001, Inf. Fusion.

[7]  S. Acton,et al.  Image enhancement using a contrast measure in the compressed domain , 2003, IEEE Signal Processing Letters.

[8]  Vps Naidu Discrete Cosine Transform-based Image Fusion , 2010 .

[9]  Luciano Alparone,et al.  Assessment of pyramid-based multisensor image data fusion , 1998, Remote Sensing.

[10]  Jinshan Tang,et al.  A new contrast measure based image enhancement algorithm in the DCT domain , 2003, SMC'03 Conference Proceedings. 2003 IEEE International Conference on Systems, Man and Cybernetics. Conference Theme - System Security and Assurance (Cat. No.03CH37483).

[11]  Gilbert Strang,et al.  The Discrete Cosine Transform , 1999, SIAM Rev..

[12]  B. S. Manjunath,et al.  Multisensor Image Fusion Using the Wavelet Transform , 1995, CVGIP Graph. Model. Image Process..

[13]  Rick S. Blum Robust image fusion using a statistical signal processing approach , 2005, Inf. Fusion.

[14]  Eero P. Simoncelli,et al.  Image quality assessment: from error visibility to structural similarity , 2004, IEEE Transactions on Image Processing.