Fully spatially adaptive smoothing parameter estimation for Markov random field super-resolution mapping of remotely sensed images-Reference-Cited by-同舟云学术

Fully spatially adaptive smoothing parameter estimation for Markov random field super-resolution mapping of remotely sensed images

Published:2015-06 Issue:11 Volume:36 Page:2851-2879
ISSN:0143-1161
Container-title:International Journal of Remote Sensing
language:en
Short-container-title:International Journal of Remote Sensing

Author:

Aghighi H.¹²,Trinder J.¹,Lim S.¹,Tarabalka Y.³

Affiliation:

1. Surveying and Geospatial Engineering, School of Civil and Environmental Engineering, The University of New South Wales, Sydney, NSW 2052, Australia

2. Department of Remote Sensing & GIS, Faculty of Earth Science, Shahid Beheshti University, Tehran, Iran

3. Inria Sophia-Antipolis Méditerranée, TITANE Team, 06902 Sophia Antipolis, France

Publisher

Informa UK Limited

Subject

General Earth and Planetary Sciences

Link

https://www.tandfonline.com/doi/pdf/10.1080/01431161.2015.1049381

Reference43 articles.

1. Dynamic Block-Based Parameter Estimation for MRF Classification of High-Resolution Images

2. Hyperspectral Data Geometry-Based Estimation of Number of Endmembers Using p-Norm-Based Pure Pixel Identification Algorithm

3. Optimal ground-based sampling for remote sensing investigations: estimating the regional meant

4. Issues of uncertainty in super-resolution mapping and their implications for the design of an inter-comparison study

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