6 April 1995 Multiresolution wavelet techniques for noisy inverse-sensing problems
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Abstract
One of the generic image/signal processing problems is how to restore accurately the first order point singularity feature having the discontinuity of the first derivative that is furthermore masked with nosy clutter environment. This is known as the class of ill-condition inverse problem in a real world environment. Specifically, given the noisy sensor data, how to reconstruct the unknown singularity as the feature of the unknown source/object. We consider the rooftop singularity for the noisy sensor inverse problem, and demonstrate that the multiresolution paradigm-wavelet transform is useful to restore the source/object singularity.
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Harold H. Szu, Harold H. Szu, Sheng Zhong, Sheng Zhong, Lei Xu, Lei Xu, Qing-Yun Shi, Qing-Yun Shi, Min-Teh Cheng, Min-Teh Cheng, Ke Chen, Ke Chen, Huisheng Chi, Huisheng Chi, Che Li, Che Li, } "Multiresolution wavelet techniques for noisy inverse-sensing problems", Proc. SPIE 2491, Wavelet Applications II, (6 April 1995); doi: 10.1117/12.205375; https://doi.org/10.1117/12.205375
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