Image Fusion Technique using Multi-resolution Singular Value Decomposition

By V. Naidu. 2011

312 citations recorded by the source corpus.

A novel image fusion technique based on multi-resolution singular value decomposition (MSVD) has been presented and evaluated. The performance of this algorithm is compared with that of well known image fusion technique using wavelets. It is observed that image fusion by MSVD perform almost similar to that of wavelets. It is computationally very simple and it could be well suited for real time applications. Moreover, MSVD does not have a fixed set of basis vectors like FFT, DCT and wavelet etc. and its basis vectors depend on the data set.Defence Science Journal, 2011, 61(5), pp.479-484, DOI:http://dx.doi.org/10.14429/dsj.61.705

Subfields: Computer Vision and Pattern Recognition, Media Technology

View Paper: https://www.semanticscholar.org/paper/427a7e1f0cf5f1ae2150d16b6ebcca6ded265e2e

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Vision and Pattern Recognition

1. Qi Feng
2. Renhua Wang
3. Chang Li
4. Jing Li
5. Hongtao Huo

In Media Technology

1. Qi Feng
2. Renhua Wang
3. Chang Li
4. Jing Li
5. Hongtao Huo

Citations in the corpus

• AttentionFGAN: Infrared and Visible Image Fusion Using Attention-Based Generative Adversarial Networks (2021, methodology): “The typical MST based methods include laplacian pyramid transform (LP) [8], wavelet transform (Wavelet) [9], ratio of low pass pyramid (RP) [10], multi-resolution singular value decomposition (MSVD) [11], complex wavelet transform (DTCWT) [12] and curvelet transform (CVT) [13].”