Comparison of three image fusion methods
2014-04-09
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Image fusion can be defined as the process of combining two or more different images into a
new single image retaining salient features from each image with extended information
content. For example Infrared and visible images are fused to help pilots landing in poor
weather, visible and microwave images are fused to detect weapons and Magnetic Resonance
and Computed Tomographic images are fused for medical diagnosis.
The fusion process should preserve all relevant information in the fused image, should reduce
noise and should suppress any artifacts in the fused image.
Two approaches to image fusion are:
1. Spatial Fusion
2. Transform fusion.
In Spatial fusion, the pixel values from the source images are manipulated in spatial domain
to calculate the activity measure to form the pixel of the composite image at that location.
Transform fusion uses transform for representing the source image suitable in a form to
calculate
new single image retaining salient features from each image with extended information
content. For example Infrared and visible images are fused to help pilots landing in poor
weather, visible and microwave images are fused to detect weapons and Magnetic Resonance
and Computed Tomographic images are fused for medical diagnosis.
The fusion process should preserve all relevant information in the fused image, should reduce
noise and should suppress any artifacts in the fused image.
Two approaches to image fusion are:
1. Spatial Fusion
2. Transform fusion.
In Spatial fusion, the pixel values from the source images are manipulated in spatial domain
to calculate the activity measure to form the pixel of the composite image at that location.
Transform fusion uses transform for representing the source image suitable in a form to
calculate
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