Fusion Research of Remote Sensing Image Based on Compressive Sensing

Abstract:

Compressive Sensing provides a new method of signal processing, when the image signal is sparse or can be com-pressed, it is possible to substantially lower than the Nyquist sampling rate, the sampling mode of the image signal is sampled, and by recovery algorithms to restore the image signal. This theory can greatly reduce the amount of data calculated in the storage, processing and transmission of the image signal. Based on this theory, the paper presents the method of remote sensing image fusion in compressed sensing domain. Firstly, the image for fast Fourier transform and measurement sampling, namely to obtain the compressed perception domain data, and then using the weighted data fusion, the final fused image is obtained by solving the optimization problem of the reconstructed image. Through the experimental proved that, this fusion method deal less data but fusion effect good.

• Periodical: Applied Mechanics and Materials (Volumes 380-384)
• Pages: 3637-3642
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.380-384.3637
• Online since: August 2013
• Authors: Chao Wei, Dong Mei Liu, Fan Wang, Ling Yan Chen
• Keywords: Compressive Sensing, Image Fusion, Remote Sensing Image

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