scholarly journals Spatial Resolution Improvement of Thermal Infrared Images by Learning of Real Patch Pairs

2020 ◽  
Author(s):  
Hideaki Osako ◽  
Katsuya Kondo ◽  
Kazu Mishiba
Keyword(s):  
Spatial Resolution ◽  
Thermal Infrared ◽  
Infrared Images ◽  
Thermal Infrared Images ◽  
Resolution Improvement

Mapping the volcanic and postvolcanic activity and its revealing on thermal infrared satellite images of high spatial resolution

2019 ◽  
Vol 953 (11) ◽  
pp. 56-64
Author(s):  
M.Yu. Grischchenko ◽  
A.V. Ustyukhina
Keyword(s):  
Northern Hemisphere ◽  
Spatial Resolution ◽  
Satellite Images ◽  
High Spatial Resolution ◽  
Thermal Infrared ◽  
Infrared Images ◽  
Thermal Infrared Images ◽  
Active Volcanoes

The article deals with revealing the volcanic and postvolcanic activity on the thermal infrared images of high spatial resolution (ASTER, TM, ETM +, TIRS) and mapping based on the results of their interpretation. Active volcanoes of the temperate and subpolar zones of the Northern Hemisphere are considered

scholarly journals Multisensor Fusion of Landsat Images for High-Resolution Thermal Infrared Images Using Sparse Representations

2017 ◽  
Vol 2017 ◽  
pp. 1-10 ◽  
Author(s):  
Hong Sung Jin ◽  
Dongyeob Han
Keyword(s):  
High Resolution ◽  
Sparse Representation ◽  
Spatial Resolution ◽  
Land Surface ◽  
Spectral Response ◽  
Thermal Infrared ◽  
Environmental Research ◽  
Infrared Images ◽  
Thermal Infrared Images ◽  
Thermal Band

Land surface temperature (LST) is an important parameter in the analysis of climate and human-environment interactions. Landsat Earth observation satellite data including a thermal band have been used for environmental research and applications; however, the spatial resolution of this thermal band is relatively low. This study investigates an efficient method of fusing Landsat panchromatic and thermal infrared images using a sparse representation (SR) technique. The application of SR is used for the estimation of missing details of the available thermal infrared (TIR) image to enhance its spatial features. First, we propose a method of building a proper dictionary considering the spatial resolution of the original thermal image. Second, a sparse representation relation between low- and high-resolution images is constructed in terms of the Landsat spectral response. We then compare the fused images created with different sampling factors and patch sizes. The results of both qualitative and quantitative evaluation show that the proposed method improves spatial resolution and preserves the thermal properties of basic LST data for use with environmental problems.

scholarly journals Increasing the spatial resolution of thermal infrared images using cokriging

2011 ◽  
Vol 3 ◽  
pp. 117-122 ◽  
Author(s):  
V.F. Rodríguez-Galiano ◽  
E. Pardo-Igúzquiza ◽  
M. Chica-Olmo ◽  
J.P. Rigol-Sánchez
Keyword(s):  
Spatial Resolution ◽  
Thermal Infrared ◽  
Infrared Images ◽  
Thermal Infrared Images

scholarly journals Transformations in the Photogrammetric Co-Processing of Thermal Infrared Images and RGB Images

Sensors ◽  
2021 ◽  
Vol 21 (15) ◽  
pp. 5061
Author(s):  
Adam Dlesk ◽  
Karel Vach ◽  
Karel Pavelka
Keyword(s):  
Structure From Motion ◽  
Thermal Infrared ◽  
Processing Method ◽  
Spatial Transformation ◽  
Infrared Images ◽  
Low Resolution ◽  
Thermal Infrared Images ◽  
Rgb Images ◽  
Motion Method

The photogrammetric processing of thermal infrared (TIR) images deals with several difficulties. TIR images ordinarily have low-resolution and the contrast of the images is very low. These factors strongly complicate the photogrammetric processing, especially when a modern structure from motion method is used. These factors can be avoided by a certain co-processing method of TIR and RGB images. Two of the solutions of co-processing were suggested by the authors and are presented in this article. Each solution requires a different type of transformation–plane transformation and spatial transformation. Both types of transformations are discussed in this paper. On the experiments that were performed, there are presented requirements, advantages, disadvantages, and results of the transformations. Both methods are evaluated mainly in terms of accuracy. The transformations are presented on suggested methods, but they can be easily applied to different kinds of methods of co-processing of TIR and RGB images.

scholarly journals Applications of Satellite Thermal Infrared Images for Monitoring North Water during the Periods of Polar Darkness

1980 ◽  
Vol 25 (93) ◽  
pp. 425-438
Author(s):  
B. Dey
Keyword(s):  
Satellite Images ◽  
Open Water ◽  
Thermal Infrared ◽  
Water Area ◽  
Infrared Images ◽  
Baffin Bay ◽  
The North ◽  
Thermal Infrared Images ◽  
North Water

AbstractThe study reported here illustrates the unique value of NOAA thermal infrared (TIR) images for monitoring the North Water area in Smith Sound and northern Baffin Bay during the periods of polar darkness. Wintertime satellite images reveal that, during the months of December through February, open water and thin ice occur in a few leads and polynyas. However, in March, the areas of open water and thin ice decrease to a minimum with a consequent higher concentration of ice. Two ice dams, in northern Kennedy Channel and in northern Smith Sound, regulate the flow of ice into northern Baffin Bay and also determine the areal variations of open water and thin ice in Smith Sound.

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