Regional Image Fusion with Genetic Algorithm Optimization

Image fusion merges the complementary information of different sensors and wavelengths. Images from multiple sensors such as visible and infrared (IR) are of particular interest in many applications. We present here a multi-stage image fusion scheme for multi-sensor images. At first stage, the propo...

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Bibliographic Details
Main Authors: Ahmed, Attiq, Khurshid, Hasnat, Riaz, Muhammad Mohsin, Ghafoor, Abdul, Zaidi, Tahir
Format: Conference Proceeding
Language:English
Subjects:
genetic algorithm
Image fusion
Image segmentation
Linear programming
multi-sensor fusion
Optimization
segmentation
Sensor fusion
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Description
Summary:Image fusion merges the complementary information of different sensors and wavelengths. Images from multiple sensors such as visible and infrared (IR) are of particular interest in many applications. We present here a multi-stage image fusion scheme for multi-sensor images. At first stage, the proposed method segments the image into homogeneous regions and generates segmentation maps. At second stage, the segmentation maps are combined by an adaptive weight adjustment procedure. The third stage fuses the input images and segmentation maps via genetic algorithm based multi-objective optimization strategy. The results indicated that our proposed fusion scheme yields good quality fused images when compared against the existing image fusion method.
ISSN:2376-1172
DOI:10.1109/AMS.2015.23