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IDL - International Digital Library Of Technology & Research Volume 1, Issue 5, May 2017

Available at: www.dbpublications.org

International e-Journal For Technology And Research-2017

Image Maximization Using Multi Spectral Image Fusion Technique Ms. SAVITHA, PG Scholar, VTU University Karnataka Email ID:savib87@gmail.com

ABSTRACT (PCA) and wavelet transform (WT) image This paper reports a detailed study of a set of

image

fusion algorithms

for

its

implementation. The paper explains the theory and implementation of the effective image

fusion

experimental

algorithm

results.

and

Based

the

on

the

research and development of some image quality metrics, the fusion algorithm is evaluated. The report is an image fusion algorithm that evaluates and implements image quality metrics that are used to evaluate the implementation.

have

been

applied

to

hyperspectral and low spatial resolution satellite images with high spatial and low spectral resolution images to obtain a fusion

graph

with

apply and render the results of image fusion algorithms. The subjective (visual) and objective evaluation of the fusion image has been carried out to assess the success of the method. The objective evaluation methods include correlation coefficient (CC), root mean square error (RMSE),

relative

global

dimension

synthesis error (ERGAS) The results show that the PCA method performs better on the top of the spectral

In this study, two different image fusion techniques

fusion MATLAB is used to build the GUto

increased

spatial

resolution Like, while keeping spectral

information, and is less successful in increasing the spatial resolution. The WT is performed after the IHS transformation to improve the spatial resolution and is performed with respect to the preservation of the spectral information after the PCA and WT methods.

information as much as possible. These techniques are raw component analysis

I. INTRODUCTION Image processing techniques focus primarily on enhancing the quality of

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