Fig. 2: Effects of divisive normalisation on spectrogram pre-processing for Radio Frequency Interference (RFI) detection.
From: Spiking neural networks for radio frequency interference detection in radio astronomy
a depicts an original full LOFAR spectrogram (left) and sub-section patch (right) encoded with latency encoding spike raster (bottom, four time step exposure). RFI features are difficult to distinguish from background information. b depicts the same full spectrogram (left), sub-section patch (right) after divisive normalisation with a latency encoding spike raster (bottom, four time step exposure). The background gradient is reduced, increasing spike sparsity and making RFI features more prominent, like the three bars on the right.
