📅 October 2023
🧑 K. Marandskiy, M. Ivanovici, S. Corcodel and S. Costache
#Estimation #Soil #Gray-scale #Autonomous aerial vehicles #Fractals #Complexity theory #Remote sensing
Image complexity can provide useful information about the texture or material properties of the acquired scene. In agriculture, the complexity of remotely-sensed images of soil or land cover may reveal underlying properties of soil and/or vegetation. However, the perceived complexity may vary along scales, as a function of the altitude of the sensor. In this paper, we investigate how the fractal complexity of multispectral images acquired using an unmanned aerial vehicle varies with the altitude, in a soil roughness estimation application. We adapt a definition of the multi-spectral fractal dimension to assess the fractal complexity of images with 5 spectral bands and analyze the computed fractal complexity as a function of both altitude and the number of considered spectral bands. For the 60m and 80m altitudes, the perception of complexity is inverted with respect to expectations.
https://ai4agri.unitbv.ro/wp-content/uploads/2024/04/K_Marandskiy_WHISPERS_2023.pdf