Andrew James Dorrell

Improved motion invariant imaging with time varying shutter functions

In motion invariant photography, blur is introduced by a structured movement of the camera during capture. The structured movement results in a uniform blur which simplifies deblur through post-processing for objects moving at different speeds in a single motion plane. However motion invariance depends on the camera speed exceeding the object speed (in the image plane) by a significant amount. This can lead to noisy image results and may be a problem for implementation of the method in practice. We propose the introduction of a time varying shutter transmittance to this recently proposed computational imaging method and demonstrate through simulation how this can improve both the degree of motion invariance and the reconstructed image quality, despite a reduction in optical efficiency. Improvements in the order 6dB are demonstrated for the reconstructed, deblurred images in the presence of moderate noise. The work has the potential to bring motion invariant photography closer to use in real camera product.

Image scaling with aliasing cancellation

This paper describes a novel image scaling algorithm based on a simple orientation adaptive anti-aliasing filter. The Projection-Slice theorem of Fourier theory is applied to characterize the structure of aliasing errors along edges in scaled images. This structure is used to explain the operation of our anti-aliasing filter which removes the dominant Fourier component of the aliasing error. It is shown that edge detail may be recovered from an aliased image by applying the anti-aliasing filter to the output of a separable wide-band interpolating filter. We also describe a simple one-dimensional inverse filter that may be combined with our anti-aliasing filter to restore further detail. Comparison of our scaling algorithm with other methods demonstrates that our scaling method is generally superior to other methods in removing visible aliasing artifacts along edges. Our method also competes favorably with state-of-the-art methods in recovering edge detail, without introducing sharpening artifacts exhibited by other methods.