Abstract

This paper is aimed at the problem of Multi-focus image fusion for the same scene and has proposed a multi-focus image fusion algorithm based on NSCT [1] (The Nonsubsampled Contourlet Transform). NSCT is the sparse representation of a two-dimension piecewise smooth signals, not only satisfying the anisotropic scaling relation and having the multi-scale, multidirectional characteristics, and shift invariance, but also being able to accurately capture the image information of the contour feature and texture details. In proposed algorithm, NSCT transform is first used to decompose source images at each scale and direction to get low-pass sub-band coefficients and band-pass directional sub-band coefficients. Then, the fusion rule of weighted box-counting dimension is adopted in low-pass subband, as well as the fusion rule of local space frequency in band-pass directional sub-band. Finally, the NSCT inverse transform is employed to get the fused image. Through check experiment, our algorithm is proved to be simple and effective.

Keywords:
Contourlet Artificial intelligence Image fusion Piecewise Fusion rules Focus (optics) Pattern recognition (psychology) Computer science Algorithm Inverse Image (mathematics) Computer vision Dimension (graph theory) Fusion Mathematics Wavelet transform Wavelet

Metrics

2
Cited By
0.50
FWCI (Field Weighted Citation Impact)
12
Refs
0.75
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Advanced Image Fusion Techniques
Physical Sciences →  Engineering →  Media Technology
Image and Signal Denoising Methods
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Remote-Sensing Image Classification
Physical Sciences →  Engineering →  Media Technology

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