The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
Improving Multimodality Image Fusion through Integrate AFL and Wavelet Transform
Abstract
Image fusion based on different wavelet transform is the most commonly used image fusion method, which fuses the source pictures data in wavelet space as per some fusion rules. But, because of the uncertainties of the source images contributions to the fused image, to design a good fusion rule to incorporate however much data as could reasonably be expected into the fused picture turns into the most vital issue. On the other hand, adaptive fuzzy logic is the ideal approach to determine uncertain issues, yet it has not been utilized as a part of the outline of fusion rule. A new fusion technique based on wavelet transform and adaptive fuzzy logic is introduced in this chapter. After doing wavelet transform to source images, it computes the weight of each source images coefficients through adaptive fuzzy logic and then fuses the coefficients through weighted averaging with the processed weights to acquire a combined picture: Mutual Information, Peak Signal to Noise Ratio, and Mean Square Error as criterion.
Related Content
|
Ajay Rawat, Shivani Gambhir.
© 2017.
19 pages.
|
|
Abhijit Chandra, Srideep Maity.
© 2017.
15 pages.
|
|
Swanirbhar Majumder, Saurabh Pal.
© 2017.
26 pages.
|
|
Fouad Farouk Jabri.
© 2017.
32 pages.
|
|
Francisco Pacheco Andrade, Teresa Coelho Moreira.
© 2017.
13 pages.
|
|
Swanirbhar Majumder, Smita Majumder.
© 2017.
31 pages.
|
|
Yuanfang Guo, Oscar C. Au, Ketan Tang.
© 2017.
20 pages.
|
|
|