Application of the Singular Spectrum Analysis on electroluminescence images of thin-film photovoltaic modules
This paper discusses an application of the singular spectrum analysis method (SSA) in the context of electroluminescence (EL) images of thin-film photovoltaic (PV) modules. We propose an EL image decomposition as a sum of three components: global intensity, cell, and aperiodic components. A parametric model of the extracted signal is used to perform several image processing tasks. The cell component is used to identify interconnection lines between PV cells at sub-pixel accuracy, as well as to correct incorrect stitching of EL images. Furthermore, an explicit expression of the cell component signal is used to estimate the inverse characteristic length, a physical parameter related to the resistances in a PV module.
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