5th week of Jan

Banskota, A., Wynne, R. H., Thomas, V. A., Serbin, S. P., Kayastha, N., Gastellu-Etchegorry, J. P., & Townsend, P. A. (2013). Investigating the utility of wavelet transforms for inverting a 3-D radiative transfer model using hyperspectral data to retrieve forest LAI. Remote Sensing, 5(6), 2639-2659.

Continuum wavelength transformation is similar to CNN in deep learning. Pooling layer of CNN adjusts the resolution of 2D image. On the image, we see objects ranging from infinitesimal one to broad one. CNN imitates how human being sees. Similarly, CWT well captures signals from microscopic signal, Chlorophyll, to wide signal, such as LMA and water.