Read 'Imaging Through Turbulence' by Michael C. Roggemann available from Rakuten Kobo. Sign up today and get $5 off your first purchase. Learn how to overcome resolution limitations caused by atmospheric turbulence in Imaging Through Turbulence.
Tips for preparing a search:. Keep it simple - don't use too many different parameters. Separate search groups with parentheses and Booleans. AbstractUnder strong turbulence conditions, object’s images can be severely distorted and become unrecognizable throughout the observing time. Conventional image restoring algorithms do not perform effectively in these circumstances due to the loss of good references on the object. We propose the use a plenoptic sensor as a light field camera to map a conventional camera image onto a cell image array in the image’s sub-angular spaces.
Accordingly, each cell image on the plenoptic sensor is equivalent to the image acquired by a sub-aperture of the imaging lens. The wavefront distortion over the lens aperture can be analyzed by comparing cell images in the plenoptic sensor. By using a modified “Laplacian” metric, we can identify a good cell image in a plenoptic image sequence. The good cell image corresponds with the time and sub-aperture area on the imaging lens where wavefront distortion becomes relatively and momentarily “flat”. As a result, it will reveal the fundamental truths of the object that would be severely distorted on normal cameras.
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