机构

• 长春光学精密机械与物... [7]
• 沈阳自动化研究所 [3]
• 金属研究所 [1]
• 合肥物质科学研究院 [1]
• 西安光学精密机械研究... [1]

采集方式

• OAI收割 [13]

内容类型

• 会议论文 [9]
• 期刊论文 [4]

发表日期

• 2020 [1]
• 2018 [2]
• 2015 [1]
• 2011 [1]
• 2010 [5]
• 2009 [1]
• 更多

学科主题

筛选

浏览/检索结果: 共13条，第1-10条 帮助 条数/页： 5101520253035404550556065707580859095100 排序方式： 请选择题名升序题名降序提交时间升序提交时间降序作者升序作者降序发表日期升序发表日期降序 空间外差光谱仪光谱降噪方法研究 期刊论文  OAI收割 应用光学, 2020, 卷号: 41 -   |  收藏  |  浏览/下载：29/0  |  提交时间：2020/10/26 atmospheric monitoring  spatial heterodyne spectrometer  noise reduction  spatial heterodyne spectrum  lifting wavelet transform  大气监测  空间外差光谱仪  降噪  空间外差光谱  提升小波变换   An adaptive denoising method for Raman spectroscopy based on lifting wavelet transform 期刊论文  OAI收割 JOURNAL OF RAMAN SPECTROSCOPY, 2018, 卷号: 49, 期号: 9, 页码: 1529-1539 作者:  Chen, Hao;  Xu, Weiliang;  Broderick, Neil;  Han, Jianda   |  收藏  |  浏览/下载：18/0  |  提交时间：2021/02/02 adaptive denoising  lifting wavelet transform  noise reduction  Raman spectroscopy   An adaptive denoising method for Raman spectroscopy based on lifting wavelet transform 期刊论文  OAI收割 JOURNAL OF RAMAN SPECTROSCOPY, 2018, 卷号: 49, 期号: 9, 页码: 1529-1539 作者:  Han JD(韩建达);  Broderick, Neil;  Xu WL(徐卫良);  Chen, Hao   |  收藏  |  浏览/下载：20/0  |  提交时间：2018/10/08 adaptive denoising  lifting wavelet transform  noise reduction  Raman spectroscopy   Improved non-negative tensor Tucker decomposition algorithm for interference hyper-spectral image compression 期刊论文  OAI收割 science china-information sciences, 2015, 卷号: 58, 期号: 5 作者:  Wen Jia;  Zhao JunSuo;  Ma CaiWen;  Wang CaiLing 收藏  |  浏览/下载：65/0  |  提交时间：2015/04/03 interference hyper-spectral images  LASIS  three-dimensional lifting wavelet transform  non-negative tensor decomposition  image compression   An improved destripe noises method for TDI-CCD images (EI CONFERENCE) 会议论文  OAI收割 2011 International Conference on Mechatronic Science, Electric Engineering and Computer, MEC 2011, August 19, 2011 - August 22, 2011, Jilin, China 作者:  He B. 收藏  |  浏览/下载：22/0  |  提交时间：2013/03/25 The new destriping method using lifting wavelet transform by means of the improved threshold function is presented in this letter. It can overcome the deficiency of the hard and soft threshold function. As compared with the known threshold functions  the quality of the denoised images using the improved threshold function is much better. The results based on several image quality indexes present that the destriped images are not only visually more plausible but also suitable for analysis. Also it is reasonable in computer time and storage space to use the lifting wavelet transform. 2011 IEEE.   Destriping of TDI-CCD remote sensing image (EI CONFERENCE) 会议论文  OAI收割 2010 3rd International Conference on Advanced Computer Theory and Engineering, ICACTE 2010, August 20, 2010 - August 22, 2010, Chengdu, China 作者:  He B. 收藏  |  浏览/下载：29/0  |  提交时间：2013/03/25 Based on the characteristic of striping noise in remote sensing images  a new destriping technique for the improved threshold function using lifting wavelet transform is presented in this letter. It can overcome the shortcoming of the hard threshold function and soft threshold function. The lifting wavelet transform is easily realized. Also it is inexpensive in computer time and storage space compared with the traditional wavelet transform. We also compare the improved threshold function with some traditional threshold functions both by visual inspection and by appropriate indexes of quality of the denoised images. Evaluations of the results based on several image quality indexes indicate that image quality has been improved after destriping. The destriped images are not only visually more plausible but also suitable for computerized analysis and it did better than the existed ones. 2010 IEEE.   Destriping method using lifting wavelet transform of remote sensing image (EI CONFERENCE) 会议论文  OAI收割 2010 International Conference on Computer, Mechatronics, Control and Electronic Engineering, CMCE 2010, August 24, 2010 - August 26, 2010, Changchun, China 作者:  He B. 收藏  |  浏览/下载：30/0  |  提交时间：2013/03/25 Based on the characteristic of striping noise in remote sensing images  a new destriping noise technique for the improved multi-threshold method using lifting wavelet transform applied to remote sensing imagery is presented in this letter. Have used the lifting wavelet decomposition algorithm  the thresholds are determined by corresponding wavelet coefficients in every scale. Remote sensing imagery is so large that the algorithm must be fast and effective. The lifting wavelet transform is easily realized and inexpensive in computer time and storage space compared with the traditional wavelet transform. We also compare the method with some traditional destriping methods both by visual inspection and by appropriate indexes of quality of the denoised images. From the comparison we can see that the adaptive threshold method can preserve the spectral characteristic of the images while effectively remove striping noise and it did better than the existed ones. 2010 IEEE.   A new image fusion algorithm based on wavelet transform (EI CONFERENCE) 会议论文  OAI收割 2010 3rd International Conference on Advanced Computer Theory and Engineering, ICACTE 2010, August 20, 2010 - August 22, 2010, Chengdu, China 作者:  He X.;  Zhang Y.;  Zhang L.-G.;  Zhang L.-G. 收藏  |  浏览/下载：13/0  |  提交时间：2013/03/25 A new image fusion algorithm based on lifting wavelet transform is presented in this paper. The source images are decomposed using lifting wavelet transform respectively. Aiming at the coefficients of low frequency and high frequency  this algorithm choose a different rule to fuse the image. To the low frequency  the spatial frequency based on the neighborhood add consistency check is elected as the fusion guide. And the absolute maximum based on detail coefficients is selected as the guide to the high frequency. After that the fused image is obtained by using inverse lifting wavelet transform. Taking the ratio space frequency error and the mean gradient as criterions  experimental results demonstrate that the algorithm is very effective. 2010 IEEE.   A Blind Watermarking Algorithm Based on Lifting Wavelet Transform 会议论文  OAI收割 2nd International Conference on Information Science and Engineering (ICISE 2010), Hangzhou, China, December 4-6, 2010 作者:  Jia ZZ(贾朱植);  Cheng WS(程万胜);  Zhu HY(祝洪宇) 收藏  |  浏览/下载：24/0  |  提交时间：2012/06/06 blind watermark  lifting wavelet transform  human visual system   A Blind Watermarking Algorithm Based on Lifting Wavelet Transform and Scrambling Technology 会议论文  OAI收割 2010 International Conference on Electrical and Control Engineering (ICECE 2010), Wuhan, China, June 25-27, 2010 作者:  Jia ZZ(贾朱植);  Zhu HY(祝洪宇);  Cheng WS(程万胜) 收藏  |  浏览/下载：26/0  |  提交时间：2012/06/06 blind watermark  lifting wavelet transform  scrambling technology