Nayera Nahvi et al Int. Journal of Engineering Research and Applications www.ijera.com ISSN : 2248-9622, Vol. 4, Issue 5( Version 5), May 2014, pp.81-86 www.ijera.com 81 | Page Comparative Analysis of Various Image Fusion Techniques For Biomedical Images: A Review Nayera Nahvi, Onkar Chand Sharma Department of Electronics and Communication Engineering, PTU,Jalandhar Department of Electronics and Communication Engineering, HOD,Department of ECE,SVIET,Banur ABSTRACT- Image Fusion is a process of combining the relevant information from a set of images, into a single image, wherein the resultant fused image will be more informative and complete than any of the input images. This paper discusses implementation of DWT technique on different images to make a fused image having more information content. As DWT is the latest technique for image fusion as compared to simple image fusion and pyramid based image fusion, so we are going to implement DWT as the image fusion technique in our paper. Other methods such as Principal Component Analysis (PCA) based fusion, Intensity hue Saturation (IHS) Transform based fusion and high pass filtering methods are also discussed. A new algorithm is proposed using Discrete Wavelet transform and different fusion techniques including pixel averaging, min-max and max-min methods for medical image fusion. KEYWORDS: Principal Component Analysis, Image Fusion, Approximation and Detail Coefficients, Multiresolutional Analysis, Pixel Averaging I. INTRODUCTION Image fusion is the process by which two or more images are combined into a single image retaining the important features from each of the original images. The fusion of images is often required for images acquired from different instrument modalities or capture techniques of the same scene or objects [1]. Fusion techniques include the simplest method of pixel averaging to more complicated methods such as principal component analysis and wavelet transform fusion. Several approaches to image fusion can be distinguished, depending on whether the images are fused in the spatial domain or they are transformed into another domain, and their transforms fused [2]. The successful fusion of images acquired from different modalities or instruments is of great importance in many applications such as medical imaging, microscopic imaging, remote sensing computer vision and robotics. Many methods exist to perform image fusion [3]. The very basic one is the high pass filtering technique. Later techniques are based on Discrete Wavelet Transform, uniform rational filter bank, and Laplacian pyramid. Image fusion can be defined as the process by which several images or some of their features are combined together to form a single image fusion can be performed at different levels of the information representation. Four different levels can be distinguished i.e. signal pixel feature and symbolic levels [4]. To date the results of image fusion in areas such as remote sensing and medical imaging are primarily intended for presentation to a human observer for easier and enhanced interpretation [5]. Therefore the perception of the fused image is of paramount importance when evaluating different fusion schemes. Some generic requirements can be imposed on the fusion result [6]. a) The fused image should preserve as closely as possible all relevant information contained in the input images. b) The fusion process should not introduce any artifacts or inconsistencies which can distract or mislead the human observer or any subsequent image processing steps. c) In the fused image relevant features and noise should be suppressed to a maximum extent. d) Spatial distortion can be very well handled by frequency domain approaches on image fusion. The multi resolution analysis has become a very useful tool for analyzing remote sensing images. The discrete wavelet transform has become a very useful tool for fusion. Some other fusion methods are also there such as Laplacian- pyramid based, Curvelet transform based etc. These methods show a better performance in spatial and spectral quality of the fused image compared to other spatial methods of fusion. RESEARCH ARTICLE OPEN ACCESS