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A Robust Seamline Extraction Method for Large-Scale Orthoimages Using an Adaptive Cost A* algorithm

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 2025年

作者： Hong, Zhonghua Zhang, Zihao Hu, Shangcheng Zhou, Ruyan Pan, Haiyan Liu, Shijie Fu, Qing Tong, Xiaohua Shanghai Ocean University College of Information Technology Shanghai 201306 China Tongji University College of Surveying and GeoInformatics Shanghai 200092 China Jinggangshan University School of Electronics and Information Engineering Jiangxi 343009 China

During the mosaicking of orthophotos, geometric and radiometric inconsistencies between adjacent images can cause misalignments at the boundaries, necessitating seamline detection to bypass prominent ground features. Existing methods struggle to simultaneously circumvent various ground features such as buildings, ridges, and farmland in large-scale remote sensing images with rich ground *** leads to insufficient robustness in densely built urban areas and mountainous village regions. To address this issue, this paper proposes a seamline extraction method based on an adaptive cost A* algorithm. Initially, the seamline network is extracted as a distance-cost constraint to limit the search range of the algorithm, ensuring efficiency. Then, an improved A* algorithm is employed to optimize the seamline, utilizing an adaptive obstacle threshold and Structural Similarity Index (SSIM) to construct the heuristic function. This approach effectively bypasses prominent ground features in both urban and mountainous areas. The method does not require pre-extraction of image features and constructing a cost map;instead, it dynamically detects impassable regions in the overlapping areas during the A* path search process. Finally, the image is reprojected and mosaicked based on the seamline network. This method does not rely on auxiliary data and is more suitable for large-scale image datasets with extensive coverage. Experimental results demonstrate that, compared to existing methods and commercial software, the proposed method shows superior radiometric and geometric consistency, overcoming the robustness issues of current large-scale remote sensing image mosaicking methods. © 2008-2012 IEEE.

关键词： a algorithm optimal seamline detection orthophotos radiometric and geometric consistency

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PUBLIC TRANSPORTATION GUIDANCE algorithm BASED ON a algorithm

PUBLIC TRANSPORTATION GUIDANCE ALGORITHM BASED ON A ALGORITH...

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第11届国际模糊系统协会世界大会

作者： Liang Zou Jian-min Xu Ling-xiang Zhu (College of Traffic and Communication, South China University of Technology., Guangzhou 510640, China) (Department of Applied Mathematics, College of Science, South China Agricultural University, Guangzhou 510642, China)

This paper brings forward a new method of describing a public transportation networks and a new multi-objective public transportation guidance model. By this description, shortest path problems in bus networks are transferred into shortest path problems in normal networks. The paper extends the A* algorithm to shortest route problems in public transportation guidance systems. Finally, the developed algorithm is implemented with the bus network of Guangzhou City containing 471 routes and 1040 stops. The results indicate that the description, multi-objective model and adaptation of A* algorithm proposed in this paper are very efficient.

关键词： public transportation guidance model a algorithm routing guidance

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Research of mobile robot path planning based on improved A* algorithm

Research of mobile robot path planning based on improved A* ...

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Chinese Automation Congress (CAC)

作者： Xiao Sa Wu Huaiyu Chen Zhihuan Wuhan Univ Sci & Technol Sch Informat Sci & Engn Wuhan Peoples R China

ISBN: (数字)9781728176871

ISBN: (纸本)9781728176871

Aiming at the problem of low efficiency, large path turning angle and insufficient path smoothness of mobile robot path planning using traditional A* algorithm, an novel path planning method based on improved A* algorithm is proposed in this paper. The procedure of the proposed method is described as follows. Firstly, the grid method is used to model the working environment map of the mobile robot. Then, in order to improve the evaluation function of the A* algorithm, not only the node steering angle and the node direction angle are integrated into the actual cost function and heuristic function of the evaluation function, but also the exponential distance adjustment factor and parent node heuristic function information are added to the heuristic function. Finally, a rotation prediction method, to which the judgment of the minimum safety distance is added, is designed to optimize the two-way smoothing of the planned path. The simulation experiment results show that the path length planned by the improved A* algorithm is shorter, and the turning angle and number of turns are smaller. The algorithm designed in this paper can improve the search efficiency and adaptability of the A* algorithm, and increase the smoothness and safety of the path.

关键词： mobile robot path planning a algorithm rotation prediction

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Application and Implementation of A* algorithm in Picture Matching Path-Finding

Application and Implementation of A* Algorithm in Picture Ma...

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The 2010 International Conference on Computer Application and System Modeling(2010计算机应用与系统建模国际会议 ICCASM 2010)

作者： Zheng-hong Hu Jin Li Computer Science Department Taiyuan Normal University Taiyuan Shanxi 030012China

ISBN: (纸本)9781424472352

In game design, Artificial intelligence is an important and complex module, and path-finding algorithms are one of the most fundamental problems applied to video games. According to the feature of path -finding in Picture Matching game, this paper analyzed a* algorithm applied to the game in detail, and pointed out the composition of estimate function. Combined with practical application, the paper given its realization.

关键词： path-finding breadth-first search a algorithm estimate function

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An Improved A* algorithm in Path Planning

An Improved A* Algorithm in Path Planning

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2010 International Conference on Computer,Mechatronics, Control and Electronic Engineering (CMCE 2010)

作者： Bai Wenfeng and Han Lina The College of Electrical and Electronic Engineering,Changchun University of Technology No.2055 Yan'An Street,Jilin,130012,China Shi Yunfeng The College of Electrical and Electronic Engineering,Changchun University of Technology No.2055 Yan'An Street,Jilin,130012,China

Aimed to the path optimization problem,this paper considers these two elements:the path cost and time-consuming to reduce the complexity of the planning issue and raise a algorithm search efficiency,so that a searched... 详细信息

关键词： component a algorithm cost function the path optimization algorithm

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Enhanced A* algorithms for multiple alignments: optimal alignments for several sequences and k-opt approximate alignments for large cases

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THEORETICAL COMPUTER SCIENCE 1999年第2期210卷 341-374页

作者： Ikeda, T Imai, H Univ Tokyo Dept Informat Sci Tokyo 113 Japan

The multiple alignment of the sequences of DNA and proteins is applicable to various important fields in molecular biology. Although the approach based on Dynamic Programming is well-known for this problem, it requires enormous time and space to obtain the optimal alignment. On the other hand, this problem corresponds to the shortest path problem and the A* algorithm, which can efficiently find the shortest path with an estimator, is usable. First, this paper directly applies the A* algorithm to multiple sequence alignment problem with more powerful estimator in more than two-dimensional case and discusses the extensions of this approach utilizing an upper bound of the shortest path length and of modification of network structure. The algorithm to provide the upper bound is also proposed in this paper. The basic part of these results was originally shown in Ikeda and Imai [11]. This part is similar to the branch-and-bound techniques implemented in MSA program in Gupta ct al. [6]. Our framework is based on the edge length transformation to reduce the problem to the shortest path problem, which is more suitable to generalizations to enumerating suboptimal alignments and parametric analysis as done in Shibuya and Imai [15-17]. By this enhanced A* algorithm, optimal multiple alignments of several long sequences can be computed in practice, which is shown by computational results. Second, this paper proposes a k-group alignment algorithm for multiple alignment as a practical method for much larger-size problem of, say multiple alignments of 50-100 sequences. A basic part of these results were originally presented in Imai and Ikeda [13]. In existing iterative improvement methods for multiple alignment, the so-called group-to-group two-dimensional dynamic programming has been used, and in this respect our proposal is to extend the ordinary two-group dynamic programming to a k-group alignment programming. This extension is conceptually straightforward, and here our contribu

关键词： multiple alignment A* algorithm a algorithm group alignment

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15 Puzzle Problem Solving By Using Heuristic-Based Approaches 3

15 Puzzle Problem Solving By Using Heuristic-Based Approache...

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3rd International Conference on Intelligent Systems, Advanced Computing, and Communication, ISACC 2025

作者： Keskar, Revati Kolhe, Vaibhavi Bhadange, Piyusha Raut, Roshani Pimpri Chinchwad College of Engineering Department of Information Technology Pune India

ISBN: (纸本)9798331523893

The 15-Puzzle is one of the most famous benchmarks to test heuristic search algorithms that are challenging both in efficient state space exploration and optimizing solutions. The task in this puzzle is to fit a 4x4 grid of numbered tiles in a disordered state to a target configuration with minimal moves. This paper covers heuristic-based approaches and works with Manhattan Distance, Misplaced Tile, and Linear Conflict heuristics under an A∗ search algorithm to come up with a solution for the problem. A∗ approximates the cost that has to be made to achieve the goal state by finding the best possible solution. Each heuristic was then measured on computation time and memory usage, by first solving the initial configurations of the puzzles with A*. Then each of them compared their performance regarding the nodes expanded, the actual time of computation, and path length. Analysis with techniques of visualization will involve node exploration graphs and the graphs of effectiveness in terms of heuristics used. The results indicate that there are instances when simpler heuristics provide faster less optimal solutions and advanced ones, such as Linear Conflict, prove to be more accurate path results but with higher computations. In this case, Manhattan Distance finds a kind of balance between accuracy and efficiency, and Linear Conflict reduces the search depth at nearly solved puzzles. Although less powerful for tile movement error, its simplicity also makes it a better alternative. Conclusion Manhattan distance and linear conflict heuristics are very effective for solving the 15-puzzle problem. Specifically, linear conflict is quite useful for configurations close to being solved. Hybrid approaches to applying heuristics can be quite valuable in improving performance but still retaining solution optimality. The combination of appropriate heuristics allows such a tradeoff between speed and accuracy, with significant implications for real world AI pathfinding and robotics.

关键词： 15-Puzzle a algorithm Linear Conflict Manhattan Distance Misplaced Tile

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Multiagent Pathfinding Under Rigid, Optimization, and Uncertainty Constraints

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COMPUTER 2021年第7期54卷 111-118页

作者： Drusinsky, Doron Michael, James Bret Naval Postgrad Sch Dept Comp Sci Monterey CA 93943 USA Aerendir Inc Mountain View CA 94040 USA Naval Postgrad Sch Dept Elect & Comp Engn Monterey CA 93943 USA

Many contemporary navigation applications rely on the well-known A* algorithm for pathfinding. We present a pathfinding technique utilizing the cross-entropy method and Bayesian networks that is capable of finding pat... 详细信息

关键词： Belief Networks Entropy Multi Agent Systems Navigation Optimisation Path Planning Multiagent Pathfinding Uncertainty Constraints Contemporary Navigation Applications Cross Entropy Method Bayesian Networks Multiple Agents Rigid Optimization a algorithm Uncertainty Navigation Bayes Methods Optimization Multi Agent Systems

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Optimal path finding algorithms based on SLSD road network model

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Journal of Southeast University(English Edition) 2010年第4期26卷 558-562页

作者：张小国王庆龚福祥东南大学仪器科学与工程学院南京210096

A solution to compute the optimal path based on a single-line-single-directional（SLSD）road network model is *** the traditional road network model,in the SLSD conceptual model,being single-directional and single-line style,a road is no longer a linkage of road nodes but abstracted as a network ***,a road node is abstracted as the linkage of two ordered single-directional *** model can describe turn restrictions,circular roads,and other real scenarios usually described using a *** a computing framework for optimal path finding（OPF）is *** is proved that classical Dijkstra and a algorithms can be directly used for OPF computing of any real-world road networks by transferring a super-graph to an SLSD ***,using Singapore road network data,the proposed conceptual model and its corresponding optimal path finding algorithms are validated using a two-step optimal path finding algorithm with a pre-computing strategy based on the SLSD road network.

关键词： optimal path finding road network model conceptual model digital map vehicle navigation system a algorithm Dijkstra algorithm

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Real Time Evaluation of Grid Based Path Planning algorithms: A comparative study

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IFAC Proceedings Volumes 2014年第1期47卷 766-772页

作者： C. Saranya K. Koteswara Rao Manju Unnikrishnan Dr. V. Brinda V.R. Lalithambika M.V. Dhekane Scientist/Engineer Control Design Division Vikram Sarabhai Space Centre India Section Head Control Design Division Vikram Sarabhai Space Centre India Division Head Control Design Division Vikram Sarabhai Space Centre India Group Director Control and Guidance Design Group Vikram Sarabhai Space Centre India Deputy Director Control Guidance and Simulation Entity Vikram Sarabhai Space Centre India

Path Planning algorithms are indispensable in Autonomous Navigators. Though rover may not have prior information about the environment, path planning algorithms must be robust enough to navigate it to the target. A and D are grid based Path Planning algorithms which enable to reach the target in shortest path. Cost computations are fixed in a algorithm while re- computations are done in D algorithm, whenever new obstacles are identified. A modified version of D algorithm is presented in this paper where cost re-computation is done based on certain criterion. By reducing the number of times cost re-computation occurs, Modified D aims to produce shortest path similar to D algorithm with less memory requirements and execution time. This paper also brings out the implementation of A, D and Modified D algorithms with NXT LEGO Mindstorms kit and their evaluation in real time scenario. Comparison of the above algorithms is elicited.

关键词： Path Planning Autonomous navigators a algorithm D algorithm

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