David J. Heeger

TL;DR: Results from three empirical tests support the hypothesis that fMRI responses in human primary visual cortex (V1) depend separably on stimulus timing and stimulus contrast, and the noise in the fMRI data is independent of stimulus contrast and temporal period.

TL;DR: A modified version of the linear/energy model is presented in which striate cells mutually inhibit one another, effectively normalizing their responses with respect to stimulus contrast, and shows that the new model explains a significantly larger body of physiological data.

TL;DR: Normalization was developed to explain responses in the primary visual cortex and is now thought to operate throughout the visual system, and in many other sensory modalities and brain regions, suggesting that it serves as a canonical neural computation.

TL;DR: Two examples of jointly shiftable transforms that are simultaneously shiftable in more than one domain are explored and the usefulness of these image representations for scale-space analysis, stereo disparity measurement, and image enhancement is demonstrated.

TL;DR: It is shown that anisotropic diffusion can be seen as a robust estimation procedure that estimates a piecewise smooth image from a noisy input image and the connection to the error norm and influence function in the robust estimation framework leads to a new "edge-stopping" function based on Tukey's biweight robust estimator that preserves sharper boundaries than previous formulations and improves the automatic stopping of the diffusion.