This paper is published in Volume-3, Issue-2, 2017
Area
Image Processing
Author
Barkha Panda, Prabhakar Sharma
Org/Univ
RIT Raipur, CSVTU Bhilai, Raipur, Chattisgarh, India
Pub. Date
09 March, 2017
Paper ID
V3I2-1173
Publisher
Keywords
Image Fusion, Spatial Domain, Transform Domain Principal Component Analysis (PCA), Discrete Wavelet Transform (DWT), Curvelet Transform.

Citationsacebook

IEEE
Barkha Panda, Prabhakar Sharma. Image Fusion based on Integration of Wavelet and Curvelet Fusion Methods, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.

APA
Barkha Panda, Prabhakar Sharma (2017). Image Fusion based on Integration of Wavelet and Curvelet Fusion Methods. International Journal of Advance Research, Ideas and Innovations in Technology, 3(2) www.IJARIIT.com.

MLA
Barkha Panda, Prabhakar Sharma. "Image Fusion based on Integration of Wavelet and Curvelet Fusion Methods." International Journal of Advance Research, Ideas and Innovations in Technology 3.2 (2017). www.IJARIIT.com.

Abstract

In today’s period, there is a great impact of image registration and image fusion on many fields such civilian and defense areas to retrieve exact information about the particular image. the process in which different images of the same scene are captured as input images and those are combined in order to improvise the fused image content which gives more information and is complete than any of the input images. Different methods of image fusion technique are principal component analysis (PCA), Discrete Wavelet transforms (DWT), curvelet transform. Principal component analysis (PCA) is a spatial domain fusion technique, which deals with image pixels to reduce multidimensional data sets to lower dimensions for analysis. Discrete Wavelet transforms (DWT) and curvelet transform is the transform domain methods to integrate the input images and extract the exact required information. Discrete wavelet transform(DWT) has an impressive reputation as a tool for image processing in image denoising and image fusion application.The Curve lets transform is suited for objects which are smooth away from discontinuities cross curves. The application of the curvelet transform in image fusion would result in better fusion results than that obtained using Principal Component Analysis (PCA) and Discrete wavelet transforms (DWT) The idea behind the current research is to exhibit the enhancement in image processing parameters by implementing fusion of curvelet and wavelet using simple average and weighted average fusion method .
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