You have requested a machine translation of selected content from our databases. This functionality is provided solely for your convenience and is in no way intended to replace human translation. Neither SPIE nor the owners and publishers of the content make, and they explicitly disclaim, any express or implied representations or warranties of any kind, including, without limitation, representations and warranties as to the functionality of the translation feature or the accuracy or completeness of the translations.
Translations are not retained in our system. Your use of this feature and the translations is subject to all use restrictions contained in the Terms and Conditions of Use of the SPIE website.
20 August 2010Assessment method to fusion effect based on structural similarity comparison in fusion images
Image fusion can integrate several images of the same scene captured by several different sensors with different features
and resolutions at different time into one image. Research on quality assessment of fusion images is meaningful for
image processing course in order to improve the registration technology and fusion algorithm. Structural similarity
metric describes differences between two images by means of three variables, luminance, contrast, and spatial similarity,
which show the better evaluating capability than others objective metrics. A new assessment method to fusion effect
based on structural similarity comparison among fusion images is provided in paper. Fusion algorithms including
weighing method, principal component analysis, different pyramid methods and multi-resolution wavelet filtering is used
to create fusion images. Then the mutual structural similarity metric among fusion images obtained by different fusion
algorithms is used to evaluate the fusion effect. In some extent, the low structural similarity comparison denotes the low
quality fusion effect. Meanwhile, the experiment show also the fusion effect determined by structural similarity
comparison is accordant with the subjective evaluation. Besides, the experiment explain the method based on different
pyramid methods and multi-resolution wavelet filtering have the better fusion effect than weighing method and principal
component analysis method. Furthermore, the experiment also prove the whole image fusion system should choose the
different fusion algorithm to adjust to the different task requirement and applied circumstance in order to acquire the
optimum scene interpreting effect.
Yong Zhang,Weiqi Jin, andRui Xue
"Assessment method to fusion effect based on structural similarity comparison in fusion images", Proc. SPIE 7820, International Conference on Image Processing and Pattern Recognition in Industrial Engineering, 782021 (20 August 2010); https://doi.org/10.1117/12.866763
The alert did not successfully save. Please try again later.
Yong Zhang, Weiqi Jin, Rui Xue, "Assessment method to fusion effect based on structural similarity comparison in fusion images," Proc. SPIE 7820, International Conference on Image Processing and Pattern Recognition in Industrial Engineering, 782021 (20 August 2010); https://doi.org/10.1117/12.866763