T
Thanh Duc Do
Researcher at Vietnam National University, Hanoi
Publications - 9
Citations - 188
Thanh Duc Do is an academic researcher from Vietnam National University, Hanoi. The author has contributed to research in topics: Tilt (optics) & Edge detection. The author has an hindex of 6, co-authored 9 publications receiving 109 citations. Previous affiliations of Thanh Duc Do include Hanoi University of Science.
Papers
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Edge enhancement of potential field data using the logistic function and the total horizontal gradient
TL;DR: An edge detector method for the enhancement of potential field anomalies, based on the logistic function of the total horizontal gradient, which is tested on synthetic data calculated using 3 models, and also on real magnetic and gravity data from Vietnam to demonstrate that the method is a useful tool for the qualitative interpretation of possible field data.
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GCH_gravinv: A MATLAB-based program for inverting gravity anomalies over sedimentary basins
TL;DR: An easy-to-use graphical user interface (GUI) for determining the depth to the basement of a sedimentary basin derived from inverting its gravity anomalies by an iterative procedure using the combination of the FFT-based algorithm of Granser and the space domain technique of Cordell and Henderson.
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MagB_inv: A high performance Matlab program for estimating the magnetic basement relief by inverting magnetic anomalies
TL;DR: A MATLAB based program, including an easy-to-use graphical interface, developed to estimate 3D geometry of magnetic basement interfaces from respective gridded magnetic anomalies by a rapid iterative procedure based on a relationship between the Fourier transforms of the magnetic data and the interface topography.
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On the performance of phase-based filters for enhancing lateral boundaries of magnetic and gravity sources: a case study of the Seattle uplift
TL;DR: In this paper, the authors compared the performance of phase-based filters such as tilt derivative, theta map, normalized horizontal derivative, tilt derivative of the horizontal derivative and the total gradient, improved theta and horizontal gradient of a modified version of tilt derivative.
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LAS: A combination of the analytic signal amplitude and the generalised logistic function as a novel edge enhancement of magnetic data
TL;DR: In this article, an improved edge detection filter LAS (logistic function of the analytical signal), based on the generalised logistic function configured by the ratio of derivatives of the analytic signal, was proposed.