Fusion of Infrared and Visible Image Based on Compressed Sensing and Nonsubsampled Shearlet Transform
نویسندگان
چکیده
In order to solve storage and computation cost problems for the traditional whole sampling image fusion algorithms, a new method of infrared and visible light image fusion is put forward based on compressed sensing (CS) theory. Nonsubsampled shearlet transform (NSST) is introduced as the sparse transform. Compressed sensing is applied to fuse the high frequency subbands decomposed by NSST. The high frequency coefficients are compressed for measured values which are fused by the rules of spatial frequency weighting. Regional energy together with regional standard deviation guides the fusion of the low frequency subband. Finally, the fused image is gained through inverse NSST. The experimental results show that high-quality fused images can be obtained with only one layer NSST. The fused image quality is better than the several traditional fusion algorithms based on compressed sensing.
منابع مشابه
An Image Fusion Algorithm Based on Non-subsampled Shearlet Transform and Compressed Sensing
In order to obtain rapid fusion speed, an image fusion algorithm based on Nonsubsampled Shearlet Transform (NSST) and Compressed Sensing (CS) is presented. The source images are decomposed with NSST. Based on local area energy, the low-frequency coefficients are fused. The high-frequency coefficients are compressed, fused and reconstructed with CS. Based on global gradient, the measurements of ...
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