February 2015, Volume 2, Issue 2 JETIR (ISSN-2349-5162) JETIR1502027 Journal of Emerging Technologies and Innovative Research (JETIR) www.jetir.org 307 Review on Image Fusion and Its Techniques 1 Ms.Dhara Dharsandia, 2 Ms.Anjali Bhatt, 3 Mr.Manish Patel 1,2 PG Student, 3 Assistant Professor 1,2 Computer Department, 3 EC Department 1,2,3 B.H.Gardi College, Rajkot, Gujarat, India,Abstract - Image Fusion is one of the major research fields in image processing. Image Fusion is a process of combining the different information from a set of images, into a single image, where in the resultant fused image will be more informative and complete than any of the input images. Image fusion process can be defined as the integration of information from a number of registered images without the introduction of distortion. The objectives of this paper is to present an overview of imaging fusion and its different techniques. Image fusion techniques can improve the quality and increase the application of input images. Keywords - Decision fusion, Feature fusion,Fusion Methods, Image Fusion, Pixel fusion. Abbreviations – Computed Tomography (CT), Positron Emission tomography (PET), Magnetic resonance Imaging (MRI) INTRODUCTION 1.1 Image fusion Image fusion means the combining of two images into a single image that has the maximum information content without producing details that are non-existent in the image [1] . Image Fusion is a Process to improve the quality of information from a set of images. Important applications of the fusion of images include medical imaging, microscopic imaging, remote sensing, computer vision, and robotics. Medical image fusion is the process of registering and combining multiple images from single or multiple imaging modalities to improve the imaging quality and reduce randomness and redundancy in order to increase the clinical applicability of medical images (like CT Scan , X-ray , Diagnostic sonography , PET Scan , MRI etc. ) for diagnosis of medical problems [2] . 1.2 Levels of Fusion Fusion process may be classified into three classes: 1) pixel fusion 2) feature fusion 3) decision fusion Table 1 – Comparison of Fusion Levels pixel-level fusion Feature-level fusion . Decision-level fusion It is the lowest processing level which generates a fused image in which each pixel is determined from a set of pixels in each input image. It is the medium level fusion and employs features(like edge, shape, angle, texture, lighting area and depth of focus area) extraction on the input data so that features from each source can be jointly employed. It is the highest-level fusion. Input images are processed individually for information extraction. FUSION TECHNIQUES In the Image Fusion method the good information from each of the given images is fused together to form a resultant image whose quality is superior to any of the input images. Image fusion method can be broadly classified into two groups: 1) Spatial domain fusion method 2) Transform domain fusion method
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Review on Image Fusion and Its Techniques - JETIR · 2018. 6. 19. · In all wavelet based image fusion techniques the wavelet transforms W of the two registred input images I1(x,y)
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February 2015, Volume 2, Issue 2 JETIR (ISSN-2349-5162)
JETIR1502027 Journal of Emerging Technologies and Innovative Research (JETIR) www.jetir.org 307
Review on Image Fusion and Its Techniques
1Ms.Dhara Dharsandia, 2Ms.Anjali Bhatt, 3Mr.Manish Patel 1,2PG Student, 3Assistant Professor
1,2Computer Department, 3EC Department
1,2,3B.H.Gardi College, Rajkot, Gujarat, India,Abstract - Image Fusion is one of the major research fields in image processing.
Image Fusion is a process of combining the different information from a set of images, into a single image, where in the
resultant fused image will be more informative and complete than any of the input images. Image fusion process can be
defined as the integration of information from a number of registered images without the introduction of distortion. The
objectives of this paper is to present an overview of imaging fusion and its different techniques. Image fusion techniques can
improve the quality and increase the application of input images.