Two additional features are particularly useful in pixelwise satellite
data segmentation using neural networks: one results from local window
averaging around each pixel (MWA) and another uses a standard deviation
estimator (MWSD) instead of the average. While the former’s complexity has
already been solved to a satisfying minimum, the latter did not. This article
proposes a new algorithm that can substitute a naive MWSD, by making the
complexity of the computational process fall
from O(N2n2) to O(N2n), where N is a square input array side, and n is the moving
window’s side length. The Numba python
compiler was used to make python a competitive high-performancecomputing language in our optimizations. Our
results show efficiency benchmars
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