This paper is published in Volume-5, Issue-2, 2019
Area
Image Processing
Author
Kajal
Co-authors
Puneet Jain
Org/Univ
Adesh Institute of Engineering and Technology, Faridkot, Punjab, India
Pub. Date
11 March, 2019
Paper ID
V5I2-1238
Publisher
Keywords
Image fusion, Laplacian Pyramid Technique, Discrete Wavelet Transform (DWT)

Citationsacebook

IEEE
Kajal, Puneet Jain. Fusion of two and three colored and gray scale images using modified – Laplacian Pyramid Technique, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.

APA
Kajal, Puneet Jain (2019). Fusion of two and three colored and gray scale images using modified – Laplacian Pyramid Technique. International Journal of Advance Research, Ideas and Innovations in Technology, 5(2) www.IJARIIT.com.

MLA
Kajal, Puneet Jain. "Fusion of two and three colored and gray scale images using modified – Laplacian Pyramid Technique." International Journal of Advance Research, Ideas and Innovations in Technology 5.2 (2019). www.IJARIIT.com.

Abstract

Image fusion is a process of blending the complementary as well as the common features of a set of images, to generate a resultant image with superior information content in terms of subjective as well as objective analysis point of view. The goal of this exploration work is to build up some novel picture combination calculations and their applications in different fields, for example, split identification, multi-spectra sensor picture combination, restorative picture combination and edge location of multi-center pictures and so forth. The initial segment of this exploration work manages a novel break identification system dependent on Non-Destructive Testing (NDT) for splits in dividers smothering the assorted variety and multifaceted nature of divider pictures. It pursues diverse edge following calculations, for example, Hyperbolic Tangent (HBT) sifting and shrewd edge recognition calculation. The combination of locator reactions are performed utilizing Haar Discrete Wavelet Transform (HDWT) and most extreme guess with mean-detail picture combination calculation to get increasingly noticeable identification of split edges. In the proposed framework we have performed picture combination for two just as for three pictures. The proposed framework gives improved edge location in pictures with unrivaled edge confinement and higher PSNR.
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