Ricoh Company, Ltd.

Sharp Laboratories of America, Inc

Junlan Yang

David Geoffrey Stork

M Dirk Robinson

Christopher A Segall

Yeping Su

Kathrin Berkner

Petrus J L Van Beek

Noah Denis Bedard

Ivana Tosic

Wanmin Wu

Patrick Llull

Multiframe reconstruction combines a set of acquired images into a reconstructed image. Here, which images to acquire are selected based at least in part on the content of previously acquired images. In one approach, a set of at least three images of an object are acquired at different acquisition settings. For at least one of the images in the set, the acquisition setting for the image is determined based at least in part on the content of previously acquired images. Multiframe image reconstruction, preferably via a multi-focal display, is applied to the set of acquired images to synthesize a reconstructed image of the object.

Adaptive image acquisition and display using multi-focal display

Multiframe reconstruction combines a set of acquired images into a reconstructed image. Here, which images to acquire are selected based at least in part on the content of previously acquired images. In one approach, a set of at least three images of an object are acquired at different acquisition settings. For at least one of the images in the set, the acquisition setting for the image is determined based at least in part on the content of previously acquired images. Multiframe image reconstruction is applied to the set of acquired images to synthesize a reconstructed image of the object.

Adaptive image acquisition for multiframe reconstruction

Systems and devices for, and methods of, motion-compensated temporal filtering based on variable filter parameters. A method embodiment includes (a) determining, by a processor having memory, a pixel-related residue image based on a set of differences between a current pixel intensity of a current frame and a corresponding pixel intensity of a previous frame, wherein the corresponding pixel intensity is augmented by a motion-compensated vector of the previous frame; (b) determining an intensity weight based on the determined pixel-related residue image and a temporal filtering parameter; and (c) filtering the pixel intensity of the current frame based on the determined intensity weight and the motion compensated vector of the previous frame.

Motion-compensated temporal filtering based on variable filter parameters

Aspects of the present invention are related to systems and methods for image processing, in particular, de-noising and de-blurring.

Methods and systems for image processing

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Chicago, IL, United States of America

Junlan Yang