Stationary Wavelet Transform Image Fusion and Optimization Using Particle Swarm Optimization

Journal Title: IOSR Journals (IOSR Journal of Computer Engineering) - Year 2016, Vol 18, Issue 3

Abstract

  The complementary nature of imaging sensors of different modalities all brought a great need of image fusion to extract relevant information images. Medical image fusion using Stationary wavelet transform (SWT) and optimize parameter using particle swarm optimization (PSO) has been implemented anddemonstrated in PC MATLAB. In this paper selected images are fused and results obtained are tabulated. The objective of proposed algorithm was to maximize the total number of pixel in the edges to improve the resolution of edges details, thus being able to visualize more details in the images. In proposed algorithm, entropy is taken as selection criteria in stationary wavelet decomposition and PSNR is applied as the fitness function on particle swarm optimization to the data set The performance of proposed algorithm is measured by peak signal to noise ratio (PSNR), entropy, mean square error (MSE), standard deviation, (STD) etc

Authors and Affiliations

Amandeep Kaur , Reecha Sharma

Keywords

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  • EP ID EP143884
  • DOI -
  • Views 119
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How To Cite

Amandeep Kaur, Reecha Sharma (2016).  Stationary Wavelet Transform Image Fusion and Optimization Using Particle Swarm Optimization. IOSR Journals (IOSR Journal of Computer Engineering), 18(3), 32-38. https://europub.co.uk/articles/-A-143884