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INTRODUCTION

In this post you will get a basic idea of what basically Image Fusion is and how the research is being done on this topic. 

          The term fusion means in general an approach to extraction of information acquired in several domains. The goal of image fusion is to integrate complementary multisensor, multitemporal and multiview information into one new image containing information of such quality which cannot be achieved otherwise. The term quality, its meaning and measurement depend on the particular application.
           You will get this point when we will see the applications of Image Fusion.


THE EVOLUTION OF IMAGE FUSION RESEARCH

          ➢The first evolution of image fusion research is simple image fusion, which perform the basic pixel by pixel related operations like addition, subtraction, average and division. Normally fusion techniques rely on simple pixel operations on the input image values.

         ➢The second evolution of image fusion research is pyramid decomposition based image fusion. The primitive fusion schemes perform the fusion right on the source images, which often have serious side effects such as reducing contrast.

         ➢  The third evolution of image fusion starts with development of wavelet theory, people are using wavelet decomposition over pyramid decomposition for image fusion. Actually wavelet transform is nothing but one special type of pyramid decomposition.

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