Maximum noise fraction method reveals detail in aerial gamma-ray surveys

Dickson, B.L.; Taylor, Geoffrey

doi:10.1071/eg00073

Cited by 17 publications

(5 citation statements)

References 5 publications

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“…The MNF transform is a procedure similar to principal component analysis, and it consists of a linear transformation that maximizes the signal-to-noise ratio to rank order the images, i.e., according to image quality. This procedure is sufficient for reducing data redundancy from hyperspectral images [61], aerial gamma-ray survey data [63], radar datasets [64], and a time series of remote-sensing data [47]. Thus, the MNF is an efficient way to identify a subspace with reduced dimensionality and enable an appropriate selection of reference data.…”

Section: Reference Temporal-signature Selectionmentioning

confidence: 99%

Comparative Analysis of MODIS Time-Series Classification Using Support Vector Machines and Methods Based upon Distance and Similarity Measures in the Brazilian Cerrado-Caatinga Boundary

et al. 2015

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Abstract:We have mapped the primary native and exotic vegetation that occurs in the Cerrado-Caatinga transition zone in Central Brazil using MODIS-NDVI time series (product MOD09Q1) data over a two-year period (2011)(2012)(2013). Our methodology consists of the following steps: (a) the development of a three-dimensional cube composed of the NDVI-MODIS time series; (b) the removal of noise; (c) the selection of reference temporal curves and classification using similarity and distance measures; and (d) classification using support vector machines (SVMs). We evaluated different temporal classifications using similarity and distance measures of land use and land cover considering several combinations of attributes. Among the classification using distance and similarity measures, the best result employed the Euclidean distance with the NDVI-MODIS data by considering more than one reference temporal curve per class and adopting six mapping classes. In the majority of tests, the SVM classifications yielded better results than other methods. The best OPEN ACCESSRemote Sens. 2015, 7 12161 result among all the tested methods was obtained using the SVM classifier with a fourth-degree polynomial kernel; an overall accuracy of 80.75% and a Kappa coefficient of 0.76 were obtained. Our results demonstrate the potential of vegetation studies in semiarid ecosystems using time-series data.

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Section: Reference Temporal-signature Selectionmentioning

confidence: 99%

Comparative Analysis of MODIS Time-Series Classification Using Support Vector Machines and Methods Based upon Distance and Similarity Measures in the Brazilian Cerrado-Caatinga Boundary

et al. 2015

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“…The spectrometric anomalies reflect the heterogeneity of the subsoils, particularly the Neoproterozoic age geological formations of microgranite, whose radioactivity rate is about 3000 Cps (Figure 7). The normalized ratios K n , U n , and Th n have been calculated and integrated into a ternary image (Figure 8) by convention, K n is in Magenta, U n is in Yellow, and Th n is in Cyan (Green et al 1988; Dickson and Taylor 2000; Ghoneim et al 2021). These ratios led to a quantitative interpretation by visualization of the concentration variation for each radioactive element.…”

Section: Resultsmentioning

confidence: 99%

Mapping of favourable mining areas in the Tiouit area by multispectral remote sensing and airborne gamma-ray spectrometry coupled with geochemical data (Eastern Anti-Atlas, Morocco)

Miftah

Azzab

Attou

et al. 2022

Applied Earth Science

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The current investigation concern Tiouit region in order to perceive potential mining zones. Remote sensing data were the main component to process. In order to spot geochemical anomalies associated with the target zones, multispectral ASTER data, gamma-ray spectrometry, and stream sediment data were used. Crosta and SAM applications granted to map a spatial distribution of propylitic, phyllic, clay, and ferruginous alteration zones. The normalized ratios let the delineation of potassic alteration zones, including the Tiouit gold mine characterized by an intense alteration in the Ikniwn granodiorite. Thus, the potassic alteration zones are consistently co-located with the tectonic structures materialized by strong fracturing densities. The stream sediment geochemical investigation revealed that the cited areas have an important potential of mineralization, with high concentrations of As (136 g/t), Cu (91 g/t), Pb (141 g/t), Zn (392 g/t), Ag (3 g/t), Mo (11 g/t), Mn (0.2 g/t), and Fe (10.63 %).

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“…This procedure is very different from the conventional methods of noise removal in radar images, which operates on a single image. Therefore, this new approach using multi-components has no similarity with other methods applied to radar data, but is compatible with the procedures used in hyperspectral images [98][99][100][101], aerial gamma-ray surveys [33,34,102,103] and time-series data [35][36][37]. The key to success is in the reconstruction of a valid signal and the attenuation of noise from the PDC components.…”

Section: Discussionmentioning

confidence: 99%

“…In the hyperspectral data, linear transformation techniques are often used to eliminate noise, such as Maximum Noise Fraction (MNF) [31] and Noise-Adjusted Principal Components (NAPCs) [32]. However, these methods are also adequate to eliminate noise interferences of a larger amount of data, such as an aerial gamma-ray survey [33,34] and a time series of remote sensing data [35][36][37]. The MNF transform adopts similar arguments to the PCA to derivate its components.…”

Section: Figurementioning

confidence: 99%

Probability Density Components Analysis: A New Approach to Treatment and Classification of SAR Images

Júnior

Maciel²,

Carvalho³

et al. 2014

Remote Sensing

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Speckle noise (salt and pepper) is inherent to synthetic aperture radar (SAR), which causes a usual noise-like granular aspect and complicates the image classification. In SAR image analysis, the spatial information might be a particular benefit for denoising and mapping classes characterized by a statistical distribution of the pixel intensities from a complex and heterogeneous spectral response. This paper proposes the Probability Density Components Analysis (PDCA), a new alternative that combines filtering and frequency histogram to improve the classification procedure for the single-channel synthetic aperture radar (SAR) images. This method was tested on L-band SAR data from the Advanced Land Observation System (ALOS) Phased-Array Synthetic-Aperture Radar (PALSAR) sensor. The study area is localized in the Brazilian Amazon rainforest, northern Rondônia State (municipality of Candeias do Jamari), containing forest and land use patterns. The proposed algorithm uses a moving window over the image, estimating the probability density curve in different image components. Therefore, a single input image generates an output with multi-components. Initially the multi-components should be treated by OPEN ACCESSRemote Sens. 2014, 6 2990 noise-reduction methods, such as maximum noise fraction (MNF) or noise-adjusted principal components (NAPCs). Both methods enable reducing noise as well as the ordering of multi-component data in terms of the image quality. In this paper, the NAPC applied to multi-components provided large reductions in the noise levels, and the color composites considering the first NAPC enhance the classification of different surface features. In the spectral classification, the Spectral Correlation Mapper and Minimum Distance were used. The results obtained presented as similar to the visual interpretation of optical images from TM-Landsat and Google Maps.

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Maximum noise fraction method reveals detail in aerial gamma-ray surveys

Cited by 17 publications

References 5 publications

Comparative Analysis of MODIS Time-Series Classification Using Support Vector Machines and Methods Based upon Distance and Similarity Measures in the Brazilian Cerrado-Caatinga Boundary

Comparative Analysis of MODIS Time-Series Classification Using Support Vector Machines and Methods Based upon Distance and Similarity Measures in the Brazilian Cerrado-Caatinga Boundary

Mapping of favourable mining areas in the Tiouit area by multispectral remote sensing and airborne gamma-ray spectrometry coupled with geochemical data (Eastern Anti-Atlas, Morocco)

Probability Density Components Analysis: A New Approach to Treatment and Classification of SAR Images

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