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Blind restoration for nonuniform aerial images using nonlocal Retinex model and shearlet-based higher-order regularization

Rui Chen, Huizhu Jia, Xiaodong Xie, Wen Gao
2017 Journal of Electronic Imaging (JEI)  
To recover high-quality aerial image from its non-uniform version, we propose a novel patch-wise restoration approach based on a key observation that the degree of blurring is inevitably affected by the  ...  aerial scenes with top-level objective and subjective quality, and outperforms other state-of-the-art restoration methods.  ...  Sun et al. 30 predicted the Markov random field model of motion blur by learning a convolutional neural network and removed the non-uniform motion blur with this patch-level model.  ... 
doi:10.1117/1.jei.26.3.033016 fatcat:6itkkvmobfeubgs5ydtj3k2sly

A Method Combining Line Detection and Semantic Segmentation for Power Line Extraction from Unmanned Aerial Vehicle Images

Wenbo Zhao, Qing Dong, Zhengli Zuo
2022 Remote Sensing  
Then, based on the object-based Markov random field (OMRF), a weighted region adjacency graph (WRAG) is constructed using the distance and angle information of line segments to capture the complex interaction  ...  Power line extraction is the basic task of power line inspection with unmanned aerial vehicle (UAV) images.  ...  (Beijing, China) for providing us with UAV imagery.  ... 
doi:10.3390/rs14061367 fatcat:fqqjjoqzr5h3phhgw3inxfizku

Leveraging the Technology of Unmanned Aerial Vehicles for Developing Countries

Sheila N. Mugala, Dorothy K. Okello, Jonathan Serugunda
2020 SAIEE Africa Research Journal  
UAVs are more effective at inspecting power transmission lines than manual techniques especially in developing countries where it is expected that the power transmission lines will span over tens of thousands  ...  Developing countries are faced with the major challenge of inadequate infrastructure which can be overcome by using UAVs to make especially emergency deliveries.  ...  An object based Markov Random field with anisotropic weighted penalty is proposed in [57] to distinguish transmission line segments from other line segments against varying background.  ... 
doi:10.23919/saiee.2020.9194383 fatcat:5bee5dupubg7jezx5l4xj7nkmq

Expansion segmentation for visual collision detection and estimation

Jeffrey Byrne, Camillo J. Taylor
2009 2009 IEEE International Conference on Robotics and Automation  
Expansion segmentation is based on a new formulation of 6-DOF inertial aided TTC estimation, and a new derivation of a first order TTC uncertainty model due to subpixel quantization error and epipolar  ...  Proof of concept results are shown in a custom designed urban flight simulator and on operational flight data from a small air vehicle.  ...  of collision and non-collision of a conditional Markov random field in an expectation-maximization framework.  ... 
doi:10.1109/robot.2009.5152487 dblp:conf/icra/ByrneT09 fatcat:st2uyothubegzmvo3netejmlmi

Regional mapping of spekboom canopy cover using very high resolution aerial imagery

Dugal Harris, Jan Vlok, Adriaan van Niekerk
2018 Journal of Applied Remote Sensing  
A set of 2228 aerial images covering the study area was subsequently acquired from Chief Directorate: National Geo-spatial Information (NGI).  ...  The need for the first technique, called radiometric homogenisation, arose from the presence of problematic radiometric variation in the aerial imagery.  ...  Redundant features are then removed from this set using a search procedure based on Markov blanket filtering.  ... 
doi:10.1117/1.jrs.12.046022 fatcat:zy5b5vazuzb3xezt2izq7s37wi

2019 Index IEEE Transactions on Geoscience and Remote Sensing Vol. 57

2019 IEEE Transactions on Geoscience and Remote Sensing  
., Insect Biological Parameter Estimation Based on the Invariant Target Parameters of the Scattering Matrix; TGRS Aug. 2019 6212-6225 Hu, C., see Zhang, M., TGRS Sept. 2019 6666-6674 Hu, C., Zhang,  ...  B., Dong, X., and Li, Y., Geosynchronous SAR Tomography: Theory and First Experimental Verification Using Beidou IGSO Satellite; TGRS Sept. 2019 6591-6607 Hu, F., Wu, J., Chang, L., and Hanssen, R.F  ...  ., +, TGRS April 2019 2187-2197 Markov Random Fields Integrating Adaptive Interclass-Pair Penalty and Spectral Similarity for Hyperspectral Image Classification.  ... 
doi:10.1109/tgrs.2020.2967201 fatcat:kpfxoidv5bgcfo36zfsnxe4aj4

Computer Vision for Autonomous Vehicles: Problems, Datasets and State of the Art [article]

Joel Janai, Fatma Güney, Aseem Behl, Andreas Geiger
2021 arXiv   pre-print
As with any rapidly growing field, it becomes increasingly difficult to stay up-to-date or enter the field as a beginner.  ...  Recent years have witnessed enormous progress in AI-related fields such as computer vision, machine learning, and autonomous vehicles.  ...  [502] combine learning-based feature extraction with a Markov Random Field that employs high-order raypotentials [667] to model the image formation process and occlusions.  ... 
arXiv:1704.05519v3 fatcat:xiintiarqjbfldheeg2hsydyra

Piecewise-Planar 3D Reconstruction with Edge and Corner Regularization

Alexandre Boulch, Martin de La Gorce, Renaud Marlet
2014 Computer graphics forum (Print)  
Abstract This paper presents a method for the 3D reconstruction of a piecewise-planar surface from range images, typically laser scans with millions of points.  ...  Figure 1 : Reconstruction by [CLP10], and by our method with regularization based on area, edge length and number of corners.  ...  | where w f = a f /σ 2 h f (x) = x f + − x f − (7) It can be seen as a sum of submodular pairwise potentials in the context of Markov Random Fields (MRF).  ... 
doi:10.1111/cgf.12431 fatcat:kq5p37dzsfg6bhre6wiw2hxnma

Target Detection and Segmentation in Circular-Scan Synthetic-Aperture-Sonar Images using Semi-Supervised Convolutional Encoder-Decoders [article]

Isaac J. Sledge, Matthew S. Emigh, Jonathan L. King, Denton L. Woods, J. Tory Cobb, Jose C. Principe
2021 arXiv   pre-print
The encoder portion of the MB-CEDN extracts visual contrast features from CSAS images. These features are fed into dual decoders that perform pixel-level segmentation to mask targets.  ...  This illustrates that natural-image-based models may need to be altered to be effective for this imaging-sonar modality.  ...  Mignotte et al. explored a hierarchical, Markov-random-field approach in [41] . Fandos et al.  ... 
arXiv:2101.03603v3 fatcat:plz7jnctrvcvjjmtovhoj6tjsq

2021 Index IEEE Robotics and Automation Letters Vol. 6

2021 IEEE Robotics and Automation Letters  
-that appeared in this periodical during 2021, and items from previous years that were commented upon or corrected in 2021.  ...  LRA April 2021 2413-2420 Power Line Inspection Tasks With Multi-Aerial Robot Systems Via Signal Temporal Logic Specifications.  ...  Seo, S., +, Based Detection of Road Curbs Using Aerial Images for Autonomous Driving.  ... 
doi:10.1109/lra.2021.3119726 fatcat:lsnerdofvveqhlv7xx7gati2xu

Efficient Learning of Spatial Patterns with Multi-Scale Conditional Random Fields for Region-Based Classification

Mitchel Alioscha-Perez, Hichem Sahli
2014 Remote Sensing  
Hierarchical conditional random fields (CRF) consider both multi-scale and contextual information in a unified discriminative probabilistic framework, yet they suffer from two main drawbacks.  ...  We propose: (i) a multi-scale CRF model with novel energies that involves information related to the multi-scale image structure; and (ii) an efficient maximum margin parameters learning procedure where  ...  Such a hierarchy preserves the topology of the initial watershed lines and extracts homogeneous objects of a larger scale.  ... 
doi:10.3390/rs6086727 fatcat:wxgmsmyjkjfclka4k6xa4gmdii

Advances in image segmentation

Silvano Di Zenzo
1983 Image and Vision Computing  
He received his Ph.D. degree in EE from UMass Dartmouth in January 2008.  ...  He is now working in the DSP algorithm group of Naval Undersea Warfare Center at Newport, Rhode Island and has published four books and a few journal papers in the area of image processing and acoustic  ...  Thus, the proposed CCMRF model with bi-level line field with Gaussain weighted penalty function could preserve well the ill defined edges together with strong edges.  ... 
doi:10.1016/0262-8856(83)90019-7 fatcat:dk4eqjffqjbr5lmsgnwb4u5gem

Hyperspectral Remote Sensing Data Analysis and Future Challenges

Jose M. Bioucas-Dias, Antonio Plaza, Gustavo Camps-Valls, Paul Scheunders, Nasser Nasrabadi, Jocelyn Chanussot
2013 IEEE Geoscience and Remote Sensing Magazine  
Current sensors onboard airborne and spaceborne platforms cover large areas of the Earth surface with unprecedented spectral, spatial, and temporal resolutions.  ...  Another approach to jointly exploit spatial and spectral information is to use Markov random fields (MRFs) for the characterization of spatial information.  ...  Spatio-spectral methods that were developed use e.g. wavelet transforms to fuse multiresolution information of the image bands [21] , Markov Random Fields that model the spatial relationship between neighboring  ... 
doi:10.1109/mgrs.2013.2244672 fatcat:4tk7q6izd5hevhnrck36i5wkiy

Super-resolution: a comprehensive survey

Kamal Nasrollahi, Thomas B. Moeslund
2014 Machine Vision and Applications  
It has found practical applications in many real world problems in different fields, from satellite and aerial imaging to medical image processing, to facial image analysis, text image analysis, sign and  ...  Furthermore, common issues in super-resolution algorithms, such as imaging models and registration algorithms, optimization of the cost functions employed, dealing with color information, improvement factors  ...  providing us with his thoughtful comments and feedbacks.  ... 
doi:10.1007/s00138-014-0623-4 fatcat:wtfkpzbrwbajlebfvemtspz3um

Large-Scale Semantic 3D Reconstruction: An Adaptive Multi-resolution Model for Multi-class Volumetric Labeling

Maros Blaha, Christoph Vogel, Audrey Richard, Jan D. Wegner, Thomas Pock, Konrad Schindler
2016 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)  
Given a set of images of a scene, semantic 3D reconstruction aims to densely reconstruct both the 3D shape of the scene and a segmentation into semantic object classes.  ...  The energy defined by Eqs. (1, 2) is a generalization of the standard primal LP-relaxation of the Markov Random Field energy.  ...  The model of [17] employs a discrete, tight, convex relaxation of the standard multi-label Markov random field problem [42] in 3D, at the cost of high memory consumption and computation time.  ... 
doi:10.1109/cvpr.2016.346 dblp:conf/cvpr/BlahaVRWPS16 fatcat:fi3egfnfdncz7axqn3h2ebhqke
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