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	Features of Intraseasonal Variability Observed in the Upper-Layer Current in the Northern South China Sea 期刊论文 OAI收割 FRONTIERS IN MARINE SCIENCE, 2021, 卷号: 8, 页码: 13 作者: Xu, Wen; Shu, Yeqiang; Wang, Dongxiao; Chen, Ju; Wang, Jinghong \| 收藏 \| 浏览/下载：24/0 \| 提交时间：2022/05/26 intraseasonal variability two frequency bands northern South China Sea upper-layer circulation mesoscale eddies
	Image coding using wavelet-based compressive sampling (EI CONFERENCE) 会议论文 OAI收割 2012 5th International Symposium on Computational Intelligence and Design, ISCID 2012, October 28, 2012 - October 29, 2012, Hangzhou, China 作者: Li J.; Li J.; Li J. 收藏 \| 浏览/下载：45/0 \| 提交时间：2013/03/25 In this paper we proposed a novel coding scheme is proposed using wavelet-based CS framework for nature image. First two-dimension discrete wavelet transform (DWT) is applied to a nature image for sparse representation. After multi-scale DWT the low-frequency sub-band and high-frequency sub-bands are re-sampled separately. According to the statistical dependences among DWT coefficients we allocate different measurements to low- and high-frequency component. Then the measurements samples can be quantized. The quantize samples are entropy coded and forward correct coding (FEC). Finally the compressed streams are transmitted. At the decoder one can simply reconstruct the image via l1 minimization. Experimental results show that the proposed wavelet-based CS scheme achieves better compression performance against the relevant existing solutions.
	Displacement estimation by the phase-shiftings of fourier transform in present white noise (EI CONFERENCE) 会议论文 OAI收割 ICO20: Optical Information Processing, August 21, 2005 - August 26, 2005, Changchun, China 作者: Wu Y.-H. 收藏 \| 浏览/下载：29/0 \| 提交时间：2013/03/25 Displacement estimation is a fundamental problem in Real-time video image processing. It can be typically approached by theories based on features in spatial domain. This paper presents an algorithm which improves the theory for estimating the moving object's displacement in spatial domain by its Fourier transform frequency spectrum. Because of the characters of Fourier transform the result is based on all the features in the image. Utilizing shift theorem of Fourier transform and auto-registration the algorithm employs the phase spectrum difference in polar coordinate of two frame images sequence with the moving target1 2. The method needn't transform frequency spectrum to spatial domain after calculation comparing with the traditional algorithm which has to search Direc peak and it reduces processing time. Since the technique proposed uses all the image information including all the white noise in the image especially and it's hard to overcome the aliasing from noises but the technique can be an effective way to analyze the result in little white noise by the different characters between high and low frequency bands. It can give the displacement of moving target within 1 pixel of accuracy. Experimental evidence of this performance is presented and the mathematical reasons behind these characteristics are explained in depth. It is proved that the algorithm is fast and simple and can be used in image tracking and video image processing.