For random noise suppression of seismic data, we present a non-local Bayes （NL- Bayes） filtering algorithm. The NL-Bayes algorithm uses the Gaussian model instead of the weighted average of all similar patches in th...For random noise suppression of seismic data, we present a non-local Bayes （NL- Bayes） filtering algorithm. The NL-Bayes algorithm uses the Gaussian model instead of the weighted average of all similar patches in the NL-means algorithm to reduce the fuzzy of structural details, thereby improving the denoising performance. In the denoising process of seismic data, the size and the number of patches in the Gaussian model are adaptively calculated according to the standard deviation of noise. The NL-Bayes algorithm requires two iterations to complete seismic data denoising, but the second iteration makes use of denoised seismic data from the first iteration to calculate the better mean and covariance of the patch Gaussian model for improving the similarity of patches and achieving the purpose of denoising. Tests with synthetic and real data sets demonstrate that the NL-Bayes algorithm can effectively improve the SNR and preserve the fidelity of seismic data.展开更多
In the signal processing for metrewave radar, the reflection paths of target echoes can cause severe error in the elevation estimation for the low-angle target tracking. The exact angles of the reflection paths are un...In the signal processing for metrewave radar, the reflection paths of target echoes can cause severe error in the elevation estimation for the low-angle target tracking. The exact angles of the reflection paths are unknown beforehand, and therefore, the reflection paths can not be suppressed easily. Therefore, in this article, an improved reflection paths suppression approach is presented. A block matrix aggregate is constructed based on the possible angles of the reflection paths. Combined with the beamforming-like processing, a generalized maximum likelihood estimation is derived to optimize the estimation. Moreover, the noise reduction method based on the Toeplitz covariance matrix is used for better performance. This approach is applied to the real data collected by the low-angle tracking radar with 8-channel vertical array. The experiment results show that the reflection effects are reduced and the accuracy of the elevation estimate is improved.展开更多
ORB(oriented FAST and rotated BRIEF)特征检测算法,在模糊场景和光照变化剧烈的环境中,容易使提取的特征点的数量和匹配的正确率出现巨大的差异,同时,在图像物体的拐角处也容易出现特征点的堆叠。针对这一情况,提出了一种改进的ORB特...ORB(oriented FAST and rotated BRIEF)特征检测算法,在模糊场景和光照变化剧烈的环境中,容易使提取的特征点的数量和匹配的正确率出现巨大的差异,同时,在图像物体的拐角处也容易出现特征点的堆叠。针对这一情况,提出了一种改进的ORB特征检测算法。首先使用多尺度视网膜增强(multi-scale retinex,MSR)算法对图像进行特征增强,然后对图像进行网格划分,针对每个网格的灰度分布情况调整特征点检测时的阈值,之后采取动态区域非极大值抑制方法筛选最佳特征点。实验结果表明,相较于原ORB算法,改进后的算法提取的特征点在图像上的分布更加均匀,当亮度在80%的范围内变化时,特征点的重复率稳定在75%以上,匹配正确率平均提高了22%。展开更多
基金financially sponsored by Research Institute of Petroleum Exploration&Development(PETROCHINA)Scientific Research And Technology Development Projects(No.2016ycq02)China National Petroleum Corporation Science&Technology Development Projects(No.2015B-3712)Ministry of National Science&Technique(No.2016ZX05007-006)
文摘For random noise suppression of seismic data, we present a non-local Bayes （NL- Bayes） filtering algorithm. The NL-Bayes algorithm uses the Gaussian model instead of the weighted average of all similar patches in the NL-means algorithm to reduce the fuzzy of structural details, thereby improving the denoising performance. In the denoising process of seismic data, the size and the number of patches in the Gaussian model are adaptively calculated according to the standard deviation of noise. The NL-Bayes algorithm requires two iterations to complete seismic data denoising, but the second iteration makes use of denoised seismic data from the first iteration to calculate the better mean and covariance of the patch Gaussian model for improving the similarity of patches and achieving the purpose of denoising. Tests with synthetic and real data sets demonstrate that the NL-Bayes algorithm can effectively improve the SNR and preserve the fidelity of seismic data.
文摘In the signal processing for metrewave radar, the reflection paths of target echoes can cause severe error in the elevation estimation for the low-angle target tracking. The exact angles of the reflection paths are unknown beforehand, and therefore, the reflection paths can not be suppressed easily. Therefore, in this article, an improved reflection paths suppression approach is presented. A block matrix aggregate is constructed based on the possible angles of the reflection paths. Combined with the beamforming-like processing, a generalized maximum likelihood estimation is derived to optimize the estimation. Moreover, the noise reduction method based on the Toeplitz covariance matrix is used for better performance. This approach is applied to the real data collected by the low-angle tracking radar with 8-channel vertical array. The experiment results show that the reflection effects are reduced and the accuracy of the elevation estimate is improved.
文摘ORB(oriented FAST and rotated BRIEF)特征检测算法,在模糊场景和光照变化剧烈的环境中,容易使提取的特征点的数量和匹配的正确率出现巨大的差异,同时,在图像物体的拐角处也容易出现特征点的堆叠。针对这一情况,提出了一种改进的ORB特征检测算法。首先使用多尺度视网膜增强(multi-scale retinex,MSR)算法对图像进行特征增强,然后对图像进行网格划分,针对每个网格的灰度分布情况调整特征点检测时的阈值,之后采取动态区域非极大值抑制方法筛选最佳特征点。实验结果表明,相较于原ORB算法,改进后的算法提取的特征点在图像上的分布更加均匀,当亮度在80%的范围内变化时,特征点的重复率稳定在75%以上,匹配正确率平均提高了22%。
