Removal of salt-and-pepper noise in THEMIS infrared radiance and emissivity spectral data of the martian surface

Nowicki, K.; Edwards, C. S.; Christensen, P. R.

doi:10.1109/whispers.2013.8080598

Cited by 2 publications

(4 citation statements)

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“…The techniques applied to the ASTER data presented in this work have been extensively documented and applied to other infrared instruments (e.g., the Thermal Emission Imaging System, THEMIS; Christensen et al, 2004), and the effect of the algorithms on the data have been characterized in detail. For more information on the data processing algorithms applied to ASTER, see Edwards et al (2011), Nowicki et al (2013a), and Nowicki et al (2013b).…”

Section: Data Processing Aster Image Analysismentioning

confidence: 99%

“…ASTER L1B and AST_05 data were processed through a set of image noise reduction algorithms and were map-projected into the final, common projection for the area. First, ASTER images were processed to remove line-to-line noise, likely due to variations in the detector readout voltage (Bandfield et Edwards et al, 2011;Nowicki et al, 2013b). This line-to-line noise typically manifests itself in pushbroom imagers as a second-order spectral variation (Edwards et al, 2011).…”

Section: Data Processing Aster Image Analysismentioning

confidence: 99%

“…The algorithm applied operates across all spectral bands simultaneously, looking at interband correlations using a windowed approach with directional averaging (Nowicki et al, 2013a). Next, the data were processed through a white or "salt-and-pepper" noise removal routine (Nowicki et al, 2013b). The noise removal routine obscures subtle variations since they are sometimes interpreted to be noise and removed.…”

Section: Data Processing Aster Image Analysismentioning

confidence: 99%

“…The noise removal routine obscures subtle variations since they are sometimes interpreted to be noise and removed. This algorithm uses interband correlation of surface features and principal components analysis to identify "salt-and-pepper" noise and removes this noise from the image with no loss of spatial resolution (Nowicki et al, 2013b). After the removal of these instrumental noises, images were map-projected to a common projection and mosaicked In images B and E, we used a 12-11-10 decorrelation stretch.…”

Section: Data Processing Aster Image Analysismentioning

confidence: 99%

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Structural relationship between the Karakoram and Longmu Co fault systems, southwestern Tibetan Plateau, revealed by ASTER remote sensing

et al. 2018

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The western margin of the Tibetan Plateau is defined by the NE-striking, sinistral Longmu Co fault system and the NW-striking, dextral Karakoram fault system. The region of convergence of these two systems is remote and politically sensitive, precluding systematic geologic mapping in the field. As a consequence, there is considerable controversy regarding the relationship between these regionally important structural features. Analysis of Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) multispectral data and validation with field mapping provide new insights via the production of a lithologic map. Detailed analysis of the ASTER data shows that the two fault systems do not intersect but instead become parallel. Additionally, the geometry and sense of motion of the two fault systems imply that they are acting as a conjugate fault pair, in conjunction with the normal Angmong fault system, allowing for the extrusion of Tibetan lithosphere toward the east. GEOLOGIC SETTING The remote Ladakh Himalaya and adjacent Tibet (Fig. 1) feature several major tectonic structures. The Bangong, Shyok, and Indus-Yarlung suture zones mark the closure of ocean basins during the accretionary evolution of Tibet and the culminating event of India-Eurasia collision (e.g., Gansser, 1964; Yin and Harrison, 2000). The Karakoram fault system marks the southwestern margin of the Tibetan Plateau (e.g., Armijo et al.

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