Full text: Mapping without the sun

Figure 3d. Fused image by the morphological pyramid 
3.1 Visual examination 
From the results of the image fusion presented in Figure 3c and 
Figure 3d, Visual comparison suggests that the fused image 
improves sharpness compared to the original images. Moreover, 
compared with the result of the fusion obtained by the 
Laplacian pyramid, the result of the fusion obtained by the 
morphological pyramid is better in visual effect. Due to 
limitations of human vision in terms of distinguishing the 
number of grey levels, comparison and appreciation by visual 
methods does not reveal the exact potentials of the fusion 
methods. Hence, comparison of image statistics is attempted to 
evaluate the results obtained by the Laplacian pyramid fusion 
and the morphological pyramid fusion. 
3.2 Quantitative analysis 
In addition to visual examination, we conduct a quantitative 
analysis. The analysis of the experimental results is based on 
entropy and average gradient of an image (Table 1). The 
entropy refers to the amount of the image information content. 
The higher entropy, the better the image quality. The average 
gradient refers to the sharpness of the image. The higher 
average gradient, the better the image quality. 
In Table 1, we show that entropy and average gradient of the 
fused image by the morphological pyramid method are bigger 
than these of the fused image by the Laplacian pyramid method. 
From these results, we can conclude that the morphological 
pyramid method provides more detailed spatial information 
than the Laplacian pyramid-based fusion method. 
Average gradient 
Image focusing on the 
Image focusing on the 
Fused image by the 
Laplacian pyramid 
Fused image by the 
morphological pyramid 
Table 1. Evaluation of fused image by the Laplacian pyramid 
fusion and the morphological pyramid fusion. 
We have presented a region-based morphological pyramid 
fusion method. With the experiments carried out on multi-focus 
images, Compared experimental results pertaining to indicators 
of entropy and average gradient, the fusion method based on the 
morphological pyramid provides better visual and quantitative 
results than that of the Laplacian pyramid-based fusion for 
multi-focus image fusion. The implementation of our algorithm 
is still in a preliminary stage. However, the results obtained so 
far suggest that approach may be useful for the multifocus 
image fusion. Investigate will be more thoroughly in the future. 
Blum R. S., and Zheng Liu, 2005. Multi-Sensor image fusion 
and its applications. CRC Press in the special series on Signal 
Processing and Communications, pp 1-29. 
Burt P. J. and Andelson E. H., 1983.The Laplacian pyramid as a 
compact image code. IEEE Trans, on Communications, vol. 31, 
pp. 532-540. 
Burt P.J., Hong T.H., and Rosenfield, 198 LA segmentation and 
estimation on image region properties through the cooperatives 
hierarchical computation. IEEE Transactions on SMC, vol. 12, 
Pham D.T., Aslantas V., 1999.Depth from defocusing using a 
neural network. Pattern Recognition, vol. 32, pp. 715-727. 
Piella G., 2002.A general framework for multiresolution image 
fusion: from pixels to regions. Research report on CW1, 
Toet A., 1989.A morphological pyramidal image decomposition. 
Pattern Recognition Letters, vol. 9, pp. 255-261. 
The authors would like to express their sincere gratitude to the 
anonymous referees for pointing out several typos and for some 
very helpful comments. 
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