Analysis of Spatial Domain Techniques for Image Fusion

Abstract

Image fusion is a procedure of merging the required image information from two images of the same scene or background into a single picture and the resultant fused picture will be more informational and complete than any of the input images, which was taken for fusion. Processing image could be multi sensor, multi model, multi focal. The objective of image fusion is to extract the needed data from multiple images to generate a composite image that contains an enhanced representation of the image than any individual source image. There are so many methods by which we can do image fusion and getting the relevant information, which we are going to discuss one by one. Image fusion discovers application in the field of navigation object and character detection and recognition, medical diagnosis, satellite imaging for remote sensing and military. The aim of image fusion is to reduce the amount of data and create new images that are more suitable for the purposes of visual perception and machine processing. This thesis work, after amount of image fusion method research proposes five new spatial domain image fusion method. These methods are principal component analysis, simple maxima, simple minima, Discrete wavelet transform, intensity hue saturation. And verifies the fusion effect via real experiment. This thesis also takes the comparison of advantages of various algorithm, subjective & objective evaluation criteria is introduced which provide theory support & preparation for the above mentioned results. Systematic introduction to the basic theory of spatial domain image fusion is involved comprehensive exposition such as definitions, methods, feature is also clearly introduced, emphasized introduction is put on multiple scale analysis & also focused on the introduction of classical MATLAB GUI.