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Modified PCA Transformation with LWT for High-Resolution based Image Fusion

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Abstract

In this paper, we have adopted the combined approach to fuse images with spatial-domain and frequency-domain approach which has the advantages of both domains. The frequency-domain transformation is done with wavelet scheme, while modified principal component analysis (PCA) is used for spatial-domain transformation. Spatial-domain image fusion methods generally have poor performance because they produce spatial distortion in the fused image. The frequency domain methods have high computational complexity and provide great robustness. In this paper, we have proposed a method which is called modified LWT–PCA. The proposed method focuses on PCA transformation combined with frequency components obtained from LWT method to retain high resolution of image. Later, inverse PCA is performed to retirve the final image. Traditional discrete wavelet transform based on convolution requires massive computation and storage space. Wavelet transform based on lifting scheme can solve these computational complexity problems. Comparing to other multiscale transforms, wavelet transform provides better fused image. It has been observed that high correlation exists between the replaced components. The higher-resolution data ensures that the spectral information of the original image is maintained. We have obtained higher variance where gray level scattering is more, which is elaborated using experimental results. Other quantitative and qualitative results are presented in this paper which show that proposed method is better than other methods in literature.

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Acknowledgements

The authors thank Cesar H. Guzman Valdivia, Francisco J. Martinez Ruiz and Eric Galvan Tejada who provided expertise that greatly assisted the research. We are also grateful to Jose Maria Celaya Padilla and Arturo Moreno Baez who helped to revise this paper and in that line improved the manuscript significantly.

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Authors and Affiliations

  1. Department of Computer and Communication Engineering, Manipal University, Jaipur, India

    Amita Nandal

  2. University of Information Science and Technology, Ohrid, Macedonia

    Amita Nandal & Ninoslav Marina

  3. National Institute of Technology, Hamirpur, India

    Amita Nandal

  4. Faculty of Electrical Engineering, Autonomous University of Zacatecas, Zacatecas, Mexico

    Hamurabi Gamboa Rosales

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  1. Amita Nandal
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  2. Hamurabi Gamboa Rosales
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  3. Ninoslav Marina
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Correspondence to Amita Nandal.

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Nandal, A., Rosales, H.G. & Marina, N. Modified PCA Transformation with LWT for High-Resolution based Image Fusion. Iran J Sci Technol Trans Electr Eng 43 (Suppl 1), 141–157 (2019). https://doi.org/10.1007/s40998-018-0135-8

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  • DOI: https://doi.org/10.1007/s40998-018-0135-8

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