  Image Fusion is the process in which core information from a set of component
images is merged to form a single image, which is more informative and complete
than the component input images in quality and appearance. This paper presents
a fast and effective image fusion method for creating high quality fused images
by merging component images. In the proposed method, the input image is broken
down to a two-scale image representation with a base layer having large scale
variations in intensity, and a detail layer containing small scale details.
Here fusion of the base and detail layers is implemented by means of a Local
Edge preserving filtering based technique. The proposed method is an efficient
image fusion technique in which the noise component is very low and quality of
the resultant image is high so that it can be used for applications like
medical image processing, requiring very accurate edge preserved images.
Performance is tested by calculating PSNR and SSIM of images. The benefit of
the proposed method is that it removes noise without altering the underlying
structures of the image. This paper also presents an image zooming technique
using bilinear interpolation in which a portion of the input image is cropped
and bilinear interpolation is applied. Experimental results showed that the
when PSNR value is calculated, the noise is found to be very low for the
resultant image portion.
