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An enhanced image fusion in the spatial domain based on modified independent component analysis

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Abstract

Image Fusion (IF) couples the complementary information available in manifold images that are of the same scene into a sole image, which in turn encompasses a more precise illustration of the scene when compared with a solitary source image. The existent paper suggested IF utilizing disparate algorithms, but they suffer from too low RR, low informative as well as low-quality image. To trounce these issues, a MICA centered on an ameliorated IF in the Spatial Domain introduced. Steps i) Image Acquisition, ii) Image Enhancements, iii) image sharpening and iv) IF. Initially, the IA is performed, where the needed images are taken as of the Data Base. Next, the image sharpening is performed utilizing LSD. Finally, the IF is done utilizing the MICA is the sharpening image. Experimentation’s outcomes on proposed IF exhibited that the method attains competitive or better RR performance when weighed with the top-notch methods.

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Abbreviations

IF:

Image Fusion

RR:

Recognition Rate

ICA:

Independent Components Analysis

SD:

Spatial Domain

IA:

Image Acquisition

IE:

Image Enhancements

DB:

Data Base

HE:

Histograms Equalization

LSD:

Laplacian Second-order Derivatives

MICA:

Modified Independent Component Analysis

TD:

Transforms Domain

DFRNT:

Discrete Fractional Random Transformation

CNN:

Convolution-Neural Networks

FLD:

Fisher Linear Discriminants

LR:

Linear Regression

CDF:

Cumulative Distribution Function

IC:

Independent Components

PSNR:

Peak-to-Signal Noise

SSIM:

Structural Similarity Indexes Matrix

RMSE:

Root-Means-Square Error

UQI:

Universal Quality Indexes

UF:

Unfused Images

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Acknowledgements

We thank the anonymous referees for their useful suggestions.

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Authors and Affiliations

  1. Electronics and Telecommunication Engineering, Dr. D. Y. Patil Institute of Technology, Pimpri, India

    Deepali Sale

  2. Savitribai Phule Pune University, Pune, India

    Deepali Sale

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  1. Deepali Sale
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Contributions

All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Deepali Sale. The first draft of the manuscript was written by Deepali Sale, and all authors commented on previous versions of the manuscript.

All authors read and approved the final manuscript.

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Correspondence to Deepali Sale.

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Sale, D. An enhanced image fusion in the spatial domain based on modified independent component analysis. Multimed Tools Appl 81, 44123–44140 (2022). https://doi.org/10.1007/s11042-022-13238-8

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