Abstract

We present atmospheric degradation correction of terahertz (THz) beams based on multiscale signal decomposition and a combination of a Wiener deconvolution filter and artificial neural networks. THz beams suffer from strong attenuation by water molecules in the air. The proposed signal restoration approach finds the filter coefficients from a pair of reference signals previously measured from low- humidity conditions and current background air signals. Experimental results with two material samples of different chemical compositions demonstrate that the multiscale signal restoration technique is effective in correcting atmospheric degradation compared to individual and non-multiscale approaches.

© 2010 Optical Society of America

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