Implementation and Comparative Study of Image Fusion Methods in Frequency Domain

Conference paper
Part of the Smart Innovation, Systems and Technologies book series (SIST, volume 43)

Abstract

Complementary multi-focus and/or multi-model data from two or more different images are combined into one new image is called Image fusion. The main objective is to decrease vagueness and minimizes redundancy in the output while enhancing correlate information specific to a task. Medical images coming from different resources may often give different data. So, it is challenging task to merge two or more medical images. The fused images are very useful in medical diagnosis. In this paper, image fusion has been performed in discrete wavelet transform (DWT) and Contourlet transform (CNT). As a fusion rule, spatial techniques like Averaging, Maximum Selection and PCA is used. Experiments are performed on CT and MRI medical images. For evaluation and comparative analysis of methods, a set of standard performance measures are used. This paper’s results show that, the Contourlet method gives a good performance in medical image fusion, because it provides parabolic scaling and vanishing moments.

Keywords

Image fusion Spatial domain DWT (discrete wavelet transform) Contourlet transform 

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Copyright information

© Springer India 2016

Authors and Affiliations

  1. 1.Department of Computer EngineeringCHARUSETGujaratIndia
  2. 2.Department of Computer EngineeringADITGujaratIndia

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