Description: PDTDFB toolbox
The filter bank is described in:
The Shiftable Complex Directional Pyramid—Part I: Theoretical Aspects
The Shiftable Complex Directional Pyramid—Part II: Implementation and Applications
IEEE transaction on singnal processing, Oct. 2008
Other related papers and software are available at:
nttruong.googlepages.com
Acknowledgement: The code development is based on the matlab code of the contourlet toolbox and the steerable pyramid.-PDTDFB toolboxThe filter bank is described in: The Shiftable Complex Directional Pyramid-Part I: Theoretical Aspects The Shiftable Complex Directional Pyramid-Part II: Implementation and Applications IEEE transaction on singnal processing, Oct. 2008 Other related papers and software are available at: nttruong . googlepages.com Acknowledgement: The code development is based on the matlab code of the contourlet toolbox and the steerable pyramid. Platform: |
Size: 84992 |
Author:chan man man |
Hits:
Description: 交通信号灯的检测是复杂场景下交通灯识别的重点。采用了色彩分割与关联滤波方案进行交通灯的检测。首先，建立交通信号灯的高斯模型，利用高斯向量与多色彩空间结合的方法进行图像分割。然后，采用基于区域增长与相似性判定的关联滤波，对色彩分割后的图像进行处理。最后，使用基于canny算子的边缘提取算法获取方向指示灯轮廓特征，并使用基于改进hu不变矩和马氏距离对方向指示信号灯进行分类。-The detection of traffic lights is the focus of traffic lights recognition in complex scenes. Using color segmentation and the associated filtering scheme, the detection of traffic lights. First, the Gaussian model to establish the traffic lights, the use of Gaussian vector with multi-color space for image segmentation. Then, using the associated filter, based on regional growth and the similarity determination processing of the image color segmentation. Finally, the canny operator edge extraction algorithm to obtain the direction indicator profile feature, and use the classification based on improved hu moment invariants and the Mahalanobis distance directional signal lights. Platform: |
Size: 13312 |
Author:谷文彦 |
Hits:
Description: Block-based random image sampling is coupled with a projectiondriven
compressed-sensing recovery that encourages sparsity in
the domain of directional transforms simultaneously with a smooth
reconstructed image. Both contourlets as well as complex-valued
dual-tree wavelets are considered for their highly directional representation,
while bivariate shrinkage is adapted to their multiscale
decomposition structure to provide the requisite sparsity constraint.
Smoothing is achieved via a Wiener filter incorporated
into iterative projected Landweber compressed-sensing recovery,
yielding fast reconstruction. The proposed approach yields images
with quality that matches or exceeds that produced by a popular,
yet computationally expensive, technique which minimizes total
variation. Additionally, reconstruction quality is substantially
superior to that from several prominent pursuits-based algorithms
that do not include any smoothing Platform: |
Size: 5961728 |
Author:quang |
Hits:
Description: Using phase and magnitude information of the complex directional filter bank for texture image retri Platform: |
Size: 355328 |
Author:wang |
Hits:
Search - Complex Directional Filter