Image Stereo Matching Based on Multi-Scale Plane Set

2013 ◽  
Vol 709 ◽  
pp. 527-533 ◽  
Author(s):  
Xin Hui Jiang ◽  
Shao Jun Yu ◽  
Xing Jiang
Keyword(s):  
Dynamic Programming ◽  
Stereo Matching ◽  
Structural Model ◽  
Dynamic Programming Algorithm ◽  
Programming Method ◽  
Programming Algorithm ◽  
Dynamic Programming Method ◽  
Disparity Map ◽  
Matching Method ◽  
Multi Scale

The disparity map of dynamic programming method is poor. To overcome it, a stereo matching method based on multi-scale plane set is proposed in this paper. This method converts the structural model into the plane set. Define the key plane. Then the key planes are in a high-scale. The other planes are in the low scale. Stereo matching the multi-scale plane set using dynamic programming method. The experimental results show that: this method can solve the dynamic programming algorithm`s problem that disparity map has low matching accuracy and a lot of stripes error.

scholarly journals A New Dynamic Programming Method for UAV Image Stitching Using Optical Flow

2018 ◽  
Author(s):  
Weilong Zhang ◽  
Bingxuan Guo ◽  
Ming Li ◽  
Xuan Liao ◽  
Yuan Yao ◽  
...  
Keyword(s):  
Dynamic Programming ◽  
Optical Flow ◽  
Dynamic Programming Algorithm ◽  
Programming Algorithm ◽  
Dynamic Programming Method ◽  
Image Stitching ◽  
Dual Channel ◽  
New Energy ◽  
Uav Images ◽  
Uav Image

Dislocation is one of the major challenges in unmanned aerial vehicle (UAV) image stitching. In this paper, we propose a new dynamic programming for seamlessly stitching UAV images using optical flow. Our solution consists of two steps: Firstly, an image-matching algorithm is used to correct the images so that they are in the same coordinate system. Secondly, a new dynamic programming algorithm is develop based on the concept of a stereo dual-channel energy accumulation using optical flow. A new energy aggregation and traversal strategy is adopted in our solution, which can find a more optimal seam line for adjacent image stitching. Our algorithm overcomes the theoretical limitation of the classical Duplaquet algorithm. Experiments show that the algorithm can effectively solve the dislocation problem in UAV image stitching. Beyond that, our solution is also direction-independent, which has more adaptability and robustness for UAV images.

A cross-scale constrained dynamic programming algorithm for stereo matching

2017 ◽  
Author(s):  
Sipei Cheng ◽  
Feipeng Da ◽  
Jian Yu ◽  
Yuan Huang ◽  
Shaoyan Gai
Keyword(s):  
Dynamic Programming ◽  
Stereo Matching ◽  
Dynamic Programming Algorithm ◽  
Programming Algorithm

scholarly journals Improved stereo matching algorithm based on multi-scale fusion

2021 ◽  
Vol 39 (4) ◽  
pp. 876-882
Author(s):  
Xing Chen ◽  
Wenhai Zhang ◽  
Yu Hou ◽  
Lin Yang
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Stereo Matching ◽  
Dynamic Programming Algorithm ◽  
Good Effect ◽  
Disparity Map ◽  
Data Set ◽  
Matching Algorithm ◽  
Multi Scale ◽  
Feature Pyramid

Aiming at the low matching accuracy of local stereo matching algorithm in weak texture or discontinuous disparity areas, a stereo matching algorithm combining multi-scale fusion of convolutional neural network (CNN) and feature pyramid structure (FPN) is proposed. The feature pyramid is applied on the basis of the convolutional neural network to realize the multi-scale feature extraction and fusion of the image, which improves the matching similarity of the image blocks. The guide graph filter is used to quickly and effectively complete the cost aggregation. The disparity selection stage adapts the improvement dynamic programming algorithm to obtain the initial disparity map. The initial disparity map is refined so as to obtain the final disparity map. The algorithm is trained and tested on the image provided by Middlebury data set, and the result shows that the disparity map obtained by the algorithm has good effect.

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