Adaptive sparse spike coding : applications of neuroscience to the compression of natural images

GoldenPyramid.jpg

Figure 2: The Golden Laplacian Pyramid. To represent the edges of the image at different levels, we may use a simple recursive approach constructing progressively a set of images of decreasing sizes, from a base to the summit of a pyramid. Using simple down-scaling and up-scaling operators we may approximate well a Laplacian operator. This is represented here by stacking images on a Golden Rectangle, that is where the aspect ratio is the golden section $\phi \eqdef \frac{1+\sqrt{5}}{2}$. We present here the base image on the left and the successive levels of the pyramid in a clockwise fashion (for clarity, we stopped at level $8$). Note that here we also use $\phi^2$ (that is $\phi+1$) as the down-scaling factor so that the resolution of the pyramid images correspond across scales. Note at last that coefficient are very kurtotic: most are near zero, the distribution of coefficients has long tails.

reference


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


This work was supported by European integrated project FP6-015879, "FACETS".


TagFacets TagYear08 TagSparse TagPublicationsProceedings TagImageProcessing

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