Sonar images have complex background, low contrast, and deteriorative edges; these characteristics make it difficult for researchers to dispose the sonar objects. The multi-resolution analysis represents the signals i...Sonar images have complex background, low contrast, and deteriorative edges; these characteristics make it difficult for researchers to dispose the sonar objects. The multi-resolution analysis represents the signals in different scales efficiently, which is widely used in image processing. Wavelets are successful in disposing point discontinuities in one dimension, but not in two dimensions. The finite Ridgelet transform （FRIT） deals efficiently with the singularity in high dimension. It presents three improved denoising approaches, which are based on FRIT and used in the sonar image disposal technique. By experiment and comparison with traditional methods, these approaches not only suppress the artifacts, but also obtain good effect in edge keeping and SNR of the sonar image denoising.展开更多
基金This project was supported by the National Natural Science Foundation of China (60672034)the Research Fund for the Doctoral Program of Higher Education(20060217021)the Natural Science Foundation of Heilongjiang Province of China (ZJG0606-01)
文摘Sonar images have complex background, low contrast, and deteriorative edges; these characteristics make it difficult for researchers to dispose the sonar objects. The multi-resolution analysis represents the signals in different scales efficiently, which is widely used in image processing. Wavelets are successful in disposing point discontinuities in one dimension, but not in two dimensions. The finite Ridgelet transform （FRIT） deals efficiently with the singularity in high dimension. It presents three improved denoising approaches, which are based on FRIT and used in the sonar image disposal technique. By experiment and comparison with traditional methods, these approaches not only suppress the artifacts, but also obtain good effect in edge keeping and SNR of the sonar image denoising.
文摘为研究西江径流的演变规律，运用 M-K 法对西江流域广西境内3个代表水文站1980~2010年年径流时间序列资料进行了趋势性、突变特征分析，并进一步对各代表站逐月的径流变化趋势进行分析；运用具有多分辨率功能的复 Morlet 小波分析方法对各代表站径流进行多时间尺度周期性和近期径流演变趋势研究。通过趋势性和周期性分析可知，西江干流径流呈现减少趋势；西江径流存在5、15、22 a 这3类尺度的周期变化；从2010年以后5 a 左右，西江径流将处于一个整体相对偏枯期，之后将进入一个小幅震动的丰水期。实测2010~2013年径流显示西江来水较枯。
