Topic
Harmonic wavelet transform
About: Harmonic wavelet transform is a research topic. Over the lifetime, 9602 publications have been published within this topic receiving 247336 citations.
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42 citations
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TL;DR: A novel scheme for optical realization of wavelet transform for a one-dimensional signal is described and some preliminary experimental results are demonstrated.
Abstract: A novel scheme for optical realization of wavelet transform for a one-dimensional signal is described. Using commercially available components, the proposed system can perform wavelet transform in real time. Some preliminary experimental results are demonstrated.
42 citations
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01 Jun 2011TL;DR: The fractional wavelet filter computes the wavelet transform of a 256x256 grayscale image using only 16-bit fixed-point arithmetic on a micro-controller with less than 1.5kbyte of RAM and gives typically negligible degradations in image quality.
Abstract: Existing image wavelet transform techniques exceed the computational and memory resources of low-complexity wireless sensor nodes. In order to enable multimedia wireless sensors to use image wavelet transforms techniques to pre-process collected image sensor data, we introduce the fractional wavelet filter. The fractional wavelet filter computes the wavelet transform of a 256x256 grayscale image using only 16-bit fixed-point arithmetic on a micro-controller with less than 1.5kbyte of RAM. We comprehensively evaluate the resource requirements (RAM, computational complexity, computing time) as well as image quality of the fractional wavelet filter. We find that the fractional wavelet transform computed with fixed-point arithmetic gives typically negligible degradations in image quality. We also find that combining the fractional wavelet filter with a customized wavelet-based image coding system achieves image compression competitive to the JPEG2000 standard.
41 citations
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21 Aug 2000TL;DR: According to the computer simulation, the best rule of estimating the threshold is found, which is combined with three kinds of threshold processing methods to denoise the same noisy signal.
Abstract: This paper introduces the principle of wavelet multiresolution analysis. Four kinds of threshold selection rules and three methods of threshold processing are given. According to the computer simulation, the best rule of estimating the threshold is found, which is combined with three kinds of threshold processing methods to denoise the same noisy signal. The best method of threshold processing is obtained by comparing the performance of three methods of threshold processing that are applied to denoising.
41 citations
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01 Jan 2005
TL;DR: This paper suggests the absolute sum of the second-level detailed image of DWT as focus measure and shows that setting a threshold on the wavelet coefficients can dramatically increase the discriminative power of the focus measure in noisy condition.
Abstract: In this paper we propose a robust technique for image focus measure based on discrete wavelet transform (DWT) We suggest the absolute sum of the second-level detailed image of DWT as focus measure In the experiment the absolute-sum based measure shows equally well performance as the energy-based measure while enhancing computation efficiency Comparison to other benchmarking measures is also discussed Our measure exhibits more robustness to Gaussian noise Moreover, we show that setting a threshold on the wavelet coefficients can dramatically increase the discriminative power of the focus measure in noisy condition
41 citations