Mehran Hoodeh, Data Fusion

What is Data Fusion?

Imagine that you have two sources of satellite images:

  • The first one which is a Low-Resolution but Multi-Spectral image.
  • The second one which is a High-Resolution but Pan-Chromatic image.

Let me first discuss the above terms I used, if you are not already familiar with:

Resolution: The resolution is simply the size of each pixel of the image. For example, the pixels in an image with a resolution of 30m, are 30x30 m². So, any feature with sizes less than that cannot be precisely perceived within such an image.

Multi-Spectral: This is an advantage for a sensor in a satellite to take images in different bands of light frequencies. If you have a Multi-Spectral image, then by mixing 3 bands out of all, you can make a colorful image which can look much more natural to the eye.

Pan-Chromatic: These images are normally of high resolutions, but of low color (grey-scale).

Now, Data Fusion is the process of combining these two sources of data and take the advantage of each one to make a new image having both advantages, ie being High-Resolution and High-Color at the same time.

Classic Data Fusion:
The above mentioned method is the classic one which I have implemented in the mGIS software as it should have it as a GIS/RS software, and you can see an example shown below:

  Mehran Hoodeh, Data Fusion  
  My Innovation:
In the classic method, both images should have the same boundary (Coordinate Limits).
Now, imagine you have an image of Low Resolution from a large area, and a High-Resolution one from a smaller section of that area; but you want both images be merged as one single image, as shown below:
(I have implemented this method of Data Fusion, too, in mGIS.)
  Mehran Hoodeh, Data Fusion