Detection Of Road For Landing Of Aircraft In An Unfamiliar Environment: A Comparative Study
JISR on Computing, 2018 This paper is a comparative study about detecting straight road from satellite images. There are multiple applications of road detection. Here, only straight road is considered for use as a landing strip for aircraft emergency landing.
Ali Mobin Memon, Imran Amin
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De-Fencing and Multi-Focus Fusion Using Markov Random Field and Image Inpainting
IEEE Access, 2022 Multi-focus image fusion aims at combining source information from differently focused images. Fusion of multi-focus images has great applications in machine vision. The paper focuses on removal of fence occlusions in multi-focus images.
Hannan Adeel +2 more
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Snake based Unsupervised Texture Segmentation using Gaussian Markov Random Field Models [PDF]
, 2011 A functional for unsupervised texture segmentation is investigated in this paper. An auto-normal model based on Markov Random Fields is employed to model textures. The functional investigated here is optimized with respect to the model parameters and the
Mahmoodi, Sasan +3 more
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Computing the Cramer-Rao bound of Markov random field parameters: Application to the Ising and the Potts models [PDF]
, 2013 This letter considers the problem of computing the Cramer–Rao bound for the parameters of a Markov random field. Computation of the exact bound is not feasible for most fields of interest because their likelihoods are intractable and have intractable ...
Batatia, Hadj +8 more
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Multiscale Representations of Markov Random Fields [PDF]
IEEE Transactions on Signal Processing, 1992 Summary: Recently, a framework for multiscale stochastic modeling was introduced based on coarse-to-fine scale-recursive dynamics defined on trees. This model class has some attractive characteristics which lead to extremely efficient, statistically optimal signal and image processing algorithms. We show that this model class is also quite rich.
Mark R. Luettgen +3 more
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Unsupervised Texture Segmentation using Active Contours and Local Distributions of Gaussian Markov Random Field Parameters [PDF]
, 2012 In this paper, local distributions of low order Gaussian Markov Random Field (GMRF) model parameters are proposed as texture features for unsupervised texture segmentation.Instead of using model parameters as texture features, we exploit the variations ...
Michael Bennet +7 more
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Robust Regression-Based Markov Random Field for Hyperspectral Image Classification
IEEE Access, 2019 Recently, regression-based classifiers, such as the sparse representation classifier and collaborative representation classifier, have been proposed for hyperspectral image (HSI) classification.
Tianming Zhan +6 more
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SAR IMAGE CHANGE DETECTION BASED ON FUZZY MARKOV RANDOM FIELD MODEL [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2018 Most existing SAR image change detection algorithms only consider single pixel information of different images, and not consider the spatial dependencies of image pixels.
J. Zhao, G. Huang, Z. Zhao
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Segmentasi Citra Kanker Serviks Menggunakan Markov Random Field dan Algoritma K-Means
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi), 2021 Cervical cancer is a dangerous disease caused by malignant tumors that grow on the cervix and has globally attacked many women. Pap smear test is one of the early prevention efforts for cervical cancer. Medical personnel often have difficulty identifying
Raihana Salsabila Darma Wijaya +3 more
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Fuzzy Active Contour Model With Markov Random Field for Change Detection
IEEE Access, 2022 The traditional active contour models are sensitive to the speckle noise in the synthetic aperture radar (SAR) images. In this paper, the Markov random field (MRF) theory is incorporated into the fuzzy active contour model to detect the changes of ...
Fei Xie +5 more
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