Validating (MNF) transform to determine the least inherent dimensionality of ASTER image data of some uranium localities at Central Eastern Desert, Egypt

Shawky, Mahinaz M.; El-Arafy, Reda A.; Zalaky, Mohamed A. El; Elarif, Taha

doi:10.1016/j.jafrearsci.2018.08.022

Cited by 11 publications

(6 citation statements)

References 10 publications

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“…The MNF is a double pre-processing method applied to the images. The MNF transform consists of a transformation and reduction of noise in images (Berman, 1985;Dabiri & Lang, 2018;Green et al, 1988;Frassy et al, 2013;Shawky et al, 2019). MNF transforms multispectral data that include noisy components into channel images with increasing noise levels, it is therefore a method to separate the noise from the data and reduce computational requirements for further processing (Boardman et al, 1995).…”

Section: Minimum Noise Fraction (Mnf)mentioning

confidence: 99%

“…MNF is composed of two consecutive principal component (PC) transformations (Green et al, 1988). The first transformation of PC focuses on whitening noise by decorrelating and rescaling the noise in the data, producing data in which the noise has variance one (1) and no correlation from band to band (Shawky et al, 2019). This transformed data is then subjected to a second standard PC transformation, resulting in final outputs that are uncorrelated and are arranged in terms of decreasing information content (Research Systems, Inc., 2003).…”

Section: Minimum Noise Fraction (Mnf)mentioning

confidence: 99%

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Evolution of the Koma Bangou Gold Panning Site (Niger) From 1984 to 2020 Using Landsat Imagery

Abdoulatif

Baratoux

et al. 2021

Earth and Space Science

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Artisanal and small-scale mining (ASM) is mainly prevalent in developing countries (Abaidoo et al., 2019;S. Keita, 2001;Owusu et al., 2019). A few years ago, small-scale mining was estimated to account for 15%-20% of global non-fuel mineral production (Hentschel et al., 2002). Although the African continent is home to some of the world's most coveted mineral resources, this favorable geological context has largely failed to lead it toward an equitable and sustainable development trajectory (Hilson, 2002). In some African countries, extreme poverty (A. Keita, 2017;Owusu & Dwomoh, 2012) and crop failures due to climate change are driving rural populations, consisting mainly of farmers, to engage in artisanal mining to meet their daily needs. Artisanal mining is currently the most important rural non-farm activity in Africa (Hilson, 2020). It

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Section: Minimum Noise Fraction (Mnf)mentioning

confidence: 99%

Section: Minimum Noise Fraction (Mnf)mentioning

confidence: 99%

Evolution of the Koma Bangou Gold Panning Site (Niger) From 1984 to 2020 Using Landsat Imagery

Abdoulatif

Baratoux

et al. 2021

Earth and Space Science

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“…In the formula, F i represents the validity, and generally the validity is a range value; x, y, and z, respectively, represent the digitization of the length, width, and height of the image data. rough the validity calculation, data stability analysis can be performed, and the stabilized data can be converted again for easy use [10]; the formula is…”

Section: Art Visual Image Preprocessingmentioning

confidence: 99%

Art Visual Image Transmission Method Based on Cartesian Genetic Programming

Zhao

2021

Scientific Programming

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Because most of the traditional artistic visual image communication methods use the form of modeling and calculation, there are some problems such as long image processing time, low success rate of image visual communication, and poor visual effect. An artistic visual image communication method based on Cartesian genetic programming is proposed. The visual expression sensitivity difference method is introduced to process the image data, the neural network is used to identify the characteristics of the artistic visual image, the midpoint displacement method is used to remove the folds of the artistic visual image, and the processed image is formed under the above three links. The Cartesian genetic programming algorithm is used to encode the preprocessed image, improve the fitness function, select the algorithm to improve the operation, design the image rendering platform, input the processed image to the platform, and complete the artistic visual image transmission. The analysis of the experimental results shows that the image processing time of this method is short, the success rate of visual communication is high, and the image visual effect is good, which can obtain the image processing results satisfactory to users.

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“…The noise bands were determined by the eigenvalues less or equal to 2. Previous studies (e.g., [43]) suggested cut-off eigenvalues of 2 for maximum noise removal without disturbance of the original data, where approximately 120 dimensions were retained in this study. The noise bands were then replaced with zero values and the data were transformed back to the spectral domain by inverse MNF transformation.…”

Section: Hyperspectral Image Acquisition and Preprocessingmentioning

confidence: 99%

Detection of Magnesite and Associated Gangue Minerals using Hyperspectral Remote Sensing—A Laboratory Approach

Chung

Wang

et al. 2020

Remote Sensing

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This study introduced a detection method for magnesite and associated gangue minerals, including dolomite, calcite, and talc, based on mineralogical, chemical, and hyperspectral analyses using hand samples from thirteen different source locations and Specim hyperspectral short wave infrared (SWIR) hyperspectral images. Band ratio methods and logistic regression models were developed based on the spectral bands selected by the random forest algorithm. The mineralogical analysis revealed the heterogeneity of mineral composition for naturally occurring samples, showing various carbonate and silicate minerals as accessory minerals. The Mg and Ca composition of magnesite and dolomite varied significantly, inferring the mixture of minerals. The spectral characteristics of magnesite and associated gangue minerals showed major absorption features of the target minerals mixed with the absorption features of accessory carbonate minerals and talc affected by mineral composition. The spectral characteristics of magnesite and dolomite showed a systematic shift of the Mg-OH absorption features toward a shorter wavelength with an increased Mg content. The spectral bands identified by the random forest algorithm for detecting magnesite and gangue minerals were mainly associated with spectral features manifested by Mg-OH, CO3, and OH. A two-step band ratio classification method achieved an overall accuracy of 92% and 55.2%. The classification models developed by logistic regression models showed a significantly higher accuracy of 98~99.9% for training samples and 82–99.8% for validation samples. Because the samples were collected from heterogeneous sites all over the world, we believe that the results and the approach to band selection and logistic regression developed in this study can be generalized to other case studies of magnesite exploration.

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Validating (MNF) transform to determine the least inherent dimensionality of ASTER image data of some uranium localities at Central Eastern Desert, Egypt

Cited by 11 publications

References 10 publications

Evolution of the Koma Bangou Gold Panning Site (Niger) From 1984 to 2020 Using Landsat Imagery

Evolution of the Koma Bangou Gold Panning Site (Niger) From 1984 to 2020 Using Landsat Imagery

Art Visual Image Transmission Method Based on Cartesian Genetic Programming

Detection of Magnesite and Associated Gangue Minerals using Hyperspectral Remote Sensing—A Laboratory Approach

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