Abstract
Change detection method with multi-temporal satellite images based on Wavelet decomposition with Daubechies wavelet function (Multi Resolution Analysis), and tiling is proposed. The method allows detection of changes in time series analysis and is not sensitive to geometric distortions included in the satellite images. In this paper, the author proposed a method based on MRA as a method for extracting change points from satellite images acquired over many periods. Change detection method with multi-temporal satellite images based on Wavelet decomposition and tiling is proposed. The method allows to detect changes and is not sensitive to geometric distortions included in the satellite images. The experimental results with simulation image and a Landsat Thematic Mapper (TM) image show that more appropriate changes can be detected with the proposed method in comparison with the existing method of subtraction. When applied to simulations and real satellite images, it was confirmed that they were robust to minute nonlinear geometric distortion.
Highlights
Change detection is important for time series analysis obviously
The author examines a method of extracting change points of satellite images acquired over many periods using multi-resolution analysis (MRA)
When MRA is applied to multi-temporal satellite images, it is divided into four components: LL, LH, HL, and HH
Summary
Change detection is important for time series analysis obviously. Trend analysis of the global warming issues is needed for identifying the locations and the timing for severely damaged areas and timing for instance. The author examines a method of extracting change points of satellite images acquired over many periods using multi-resolution analysis (MRA). Extraction of change points from satellite image data acquired at each time as a method of performing the above, a method of taking a difference between images can be considered. The satellite image includes geometric distortion, and pixels resulting from the distortion are extracted as change points in the difference image. The author applied a multi-resolution analysis to the satellite image and devised a method of extracting a change point robust to nonlinear distortion by reducing the number of nodes, and confirmed the effect using a simulation image and a satellite image.
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