In this paper we derive convolutional filters for colour image whitening and decorrelation. Whilst whitening can be achieved via eigendecomposition of the image patch covariance, this operation is neither efficient nor biologically plausible. Given the shift invariance of image statistics, the covariance matrix contains repeated information which can be eliminated by solving directly for a per pixel linear operation (convolution). We formulate decorrelation as a shift and rotation invariant filtering operation and solve directly for the filter shape via non-linear least squares. This results in opponent-colour lateral inhibition filters which resemble those found in the human visual system. We also note the similarity of these filters to current interest point detectors, and perform an experimental evaluation of their use in this context.