Open AccessNew optimised region‐based multi‐scale image fusion method for thermal and visible images
Author(s) -
Aslantas Veysel,
Bendes Emre,
Kurban Rifat,
Toprak Ahmet Nusret
Publication year - 2014
Publication title -
iet image processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.401
H-Index - 45
eISSN - 1751-9667
pISSN - 1751-9659
DOI - 10.1049/iet-ipr.2012.0667
Subject(s) - pixel , artificial intelligence , image fusion , computer vision , computer science , weighting , fusion , metric (unit) , image (mathematics) , neighbourhood (mathematics) , process (computing) , pattern recognition (psychology) , image quality , mathematics , linguistics , philosophy , medicine , mathematical analysis , operations management , economics , radiology , operating system
On constructing a fused image by employing only individual pixels or a set of pixels within a small neighbourhood of the images (SIs) acquired from the same scene, pixel‐based fusion techniques suffer from some drawbacks, such as blurring effects, high sensitivity to noise and misregistration. To overcome these drawbacks, this study proposes a new region‐based image fusion method for thermal and visible images. Since different regions with certain properties need to be emphasised differently in the fused image, the corresponding regions of the SIs are optimally merged to obtain the fused image by employing multiple weighting factors (WFs). To improve the quality of the fused images, WFs were optimised by employing the differential evolution algorithm. Furthermore, a new quality metric was also developed to measure the quality of the fused images during the optimisation process. Experimental results show the feasibility of the proposed method.