Sparse Image Coding Using an Asynchronous Spiking Neural Network


All material (c) L. Perrinet. Please check the copyright notice.


Figure 1 Progressive reconstruction of the spiking image in the retina. To illustrate that the visual information is contained in the spike code, we show the theoretical reconstruction of the Lena image using the algorithm presented in the paper. This particular reconstruction on the 256x256 image used a Laplacian pyramid as the linear transform because this transform is invertible and exhibits only little cross-correlation between filters. Results are improved compared to the use of the Calderon frormula (as in [VanRullen, 01]), see Fig. 2 and we recognize the original image after only a few hundreds spikes.

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