Citation:

Welanjkar Sonam V, Rathod Sayali G, Kende Deepali N, Parmar Gangasingh K, 2023. "Image Fusion Based on Absolute Maximum Fusion Rule Using Biorthogonal Wavelet Transform" ESP Journal of Engineering & Technology Advancements  3(4)no1: 18-23.

Abstract:

In computer vision applications, one of the challenging problems is to combine the relevant information from various images of the same scene without introducing artifacts in the resultant image. Because of the different types of sensors are used in image capturing devices and their principle of sensing and also, due to the limited depth of focus of optical lenses used in camera, it is possible to get several images of the same scene providing different information. Therefore, combining different information from several images to get a new improved composite image becomes important area of research.

This work is related to the development of a system which helps to decompose the different images captured from many sensors from the same, then wavelet coefficients are extracted from that images and these coefficients are combined to form a fused image using Absolute Maximum Fusion Rule. Finally, inverse wavelet transform is used to obtain fused image. This paper focuses on the Pre-processing of Image Fusion.

References:

[1] Om Prakash, Richa Shrivastva and Ashish Khare, “BIORTHOGONAL WAVELET TRANSFORM BASED IMAGE FUSION USING ABSOLUTE MAXIMUM FUSION RULE”, Proceedings of 2013 IEEE Conference on Information and Communication Technologies (ICT 2013), Page No. 577-582.
[2] Prakash NK, “IMAGE FUSION ALGORITHM BASED ON BIORTHOGONAL WAVELET”, International Journal of Enterprise Computing and Business Systems, ISSN (Online): 2230-8849, Vol. 1 Issue 2 July 2011.
[3] V.P.S. Naidu and J.R. Raol, “Pixel-level Image Fusion using Wavelets and Principal Component Analysis”, Defence Science Journal, Vol. 58, No. 3, May 2008, Page No. 338-352.
[4] G Geetha, S.Raja Mohammad and Dr. Y.S.S.R. Murthy, “MULTIFOCUS IMAGE FUSION USING MULTIRESOLUTION APPROACH WITH BILATERAL GRADIENT BASED SHARPNESS CRITERION”, Computer Science & Information Technology (CS & IT), Page No. 103-115.
[5] Lindsay I Smith, “A tutorial on Principal Components Analysis”, February 26, 2002, Page No. 1-27.
[6] Deepak Kumar Sahu and M.P.Parsai, “Different Image Fusion Techniques – A Critical Review”, International Journal of Modern Engineering Research (IJMER), Vol. 2, Issue. 5, Sep.-Oct. 2012, Page No. 4298-4301.
[7] Shih-Gu Huang, “Wavelet for Image Fusion”.
[8] Mark Richardson, “Principal Component Analysis”, May 2009, Page No. 1-23.
[9] Gang Hong and Yun Zhang, “THE EFFECTS OF DIFFERENT TYPES OF WAVELETS ON IMAGE FUSION”, Page No. 1-6.
[10] Steven M. Ho!and, “PRINCIPAL COMPONENTS ANALYSIS (PCA)”, May 2008, Page No. 1-11.
[11] Jan Flusser, Filip Sroubek and Barbara Zitov, “Image Fusion: Principles, Methods, and Applications”, Tutorial EUSIPCO 2007, Page No. 1-60.

Keywords:

Image Fusion, Pre-processing of Image Fusion, Multi-focus images, Biorthogonal Wavelet Transform, Fusion Rules.