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Natural Image Coding in V1: How Much Use Is Orientation Selectivity?

Figure 5

Rate-distortion Curves.

Rate-distortion curve for PCA and ICA when equalizing the output variances (wPCA and wICA) and when equalizing the norm of the corresponding image bases in pixel space (oPCA and nICA). The plot shows the discrete entropy in bits (averaged over all dimensions) against the log of the squared reconstruction error . oPCA outperforms all other transforms in terms of the rate-distortion trade-off. wPCA in turn performes worst and remarkably similar to wICA. Since wPCA and wICA differ only by an orthogonal transformation, both representations are bound to the same metric. oPCA is the only transformation which has the same metric as the pixel representation according to which the reconstruction error is determined. By normalizing the length of the ICA basis vectors in the pixel space, the metric of nICA becomes more similar to the pixel basis and the performance with respect to the rate-distortion trade-off can be seen to improve considerably.

doi: https://doi.org/10.1371/journal.pcbi.1000336.g005