employee
Russian Federation
Russian Federation
VAK Russia 2.9.8
VAK Russia 2.3.1
UDC 004.93
UDC 004
The application of the two–dimensional Walsh-Hadamard transform is considered to evaluate the quality of images generated by remote monitoring devices for rolling stock and railway tracks. Purpose: to analyze the uneven distribution of the pixel spectrum intensity along the diagonal. This will facilitate a quantitative assessment of the degree of linear distortion in images of facilities belonging to “Russian Railways” JSC. Methods: image spectrum analysis by Walsh-Hadamard transformation. Results: the applicability of the proposed method for assessing the severity of linear distortions has been demonstrated. Practical significance: the proposed method can be applied for detecting various types of linear distortions, with the possibility of its subsequent implementation into automatic detection algorithms.
image quality assessment, Walsh-Hadamard transformation, two-dimensional image spectrum, Sobel operator, remote control, rolling stock, railway tracks, defects, diagnostics
1. Golovina L. A., Shlyakhova M. M. Tsifrovaya obrabotka izobrazheniy: uchebnoe posobie [Digital image processing: a tutorial]. Novosibirsk, Siberian State University of Geosystems and Technologies, 2020, 51 p. (In Russian)
2. Melkanovich A. F. Osnovy aerofotografii. Printsipy postroeniya, analiz i sintez aerofotoapparatov [Fundamentals of aerial photography. Principles of construction, analysis and synthesis of aerial cameras]. Moscow, Ministry of Defense of the USSR, 1975, 182 p. (In Russian)
3. Harmuth H. F. [Sequency Theory. Foundations and Applications]. Moscow, Mir Publishers, 1980, 574 p. (In Russian)
4. Trakhtman A. M. Vvedenie v obobshchennuyu spektralnuyu teoriyu signalov [Introduction to the generalized spectral theory of signals]. Moscow, Sovetskoe Radio Publishing House, 1972, 352 p. (In Russian)
5. Yunakovsky A. D. Garmonicheskiy analiz. Ryady Furye, preobrazovanie Furye i prilozheniya BPF [Harmonic analysis. Fourier series, Fourier transform and FFT applications]. Dolgoprudny, Intellekt Publishing House, 2024, 264 p. (In Russian)
6. Operator Sobelya [Sobel Operator], Wikipedia. Available at: http://en.wikipedia.org/wiki/Sobel_operator (accessed: May 19, 2024). (In Russian)
7. Vasilyev A. N. Programmirovanie na Python v primerakh i zadachakh [Programming in Python in examples and tasks]. Moscow, Eksmo Publishing House, 2021, 619 p. (In Russian)
