Eastman-kodak Company

Kodak Alaris Inc.

Intellectual Ventures Fund 83 LLC

Majid Rabbani

Paul W Jones

Chris W Honsinger

Kenneth Alan Parulski

Rajan L Joshi

Scott J Daly

Andrew Frederick Kurtz

Aaron Thomas Deever

Cheng-Tie Chen

Andrew Charles Gallagher

Michael E Miller

Jiebo Luo

John R Squilla

Kurt Michael Schroeder

Omid A Moghadam

Zhaohui Sun

Gabriel Fielding

Yusheng T Tsai

Jian Yang

Joseph Anthony Manico

John Randall Fredlund

Edward B Gindele

Thomas M Stephany

Craig M Smith

Paul James Kane

Rodney L Miller

Sen Wang

James C Stoffel

Thomas Allen Henderson

Robert T Gray

Donald E Olson

Andreas E Savakis

Christophe E Papin

Paul W Melnychuck

Robert Gretzinger

Bernard V Brower

Bhavan R Gandhi

Stephen P Etz

Jonathan K Riek

Arif T Erdem

Kevin Arnold Townsend

Deniz E Schildkraut

Yushing T Tsai

John E Hoover

A method of producing a stereo image from a digital video includes receiving a digital video including a plurality of digital images captured by an image capture device; and using a processor to produce stereo suitability scores for at least two digital images from the plurality of digital images. The method further includes selecting a stereo candidate image based on the stereo suitability scores; producing a stereo image from the selected stereo candidate image wherein the stereo image includes the stereo candidate image and an associated stereo companion image based on the plurality of digital images from the digital video; and storing the stereo image whereby the stereo image can be presented for viewing by a user.

Determining a stereo image from video

A print media () comprises paper or other substrate, on which image content, whether text or images are printed with accompanying hidden data (). The image content is printed with one or more normal printing process visible colorants (), while the hidden data () is printed with spectral edge markers (). The spectral edge marker materials () have a substantial spectral absorption just outside the human visible spectrum, and only slight visible absorption, which is masked by the visible colorants (). Although the hidden data is nominally visually imperceptible, an image capture device () having a visible spectral response that extends into a spectral region just outside the visible spectrum where the spectral edge marker absorption occurs, can then detect the hidden data.

Spectral visible edge marking for steganography or watermarking

A method for providing digital watermarking for text or images that uses spectral edge marking materials () printed on a print media () to embed hidden data (). The spectral edge markers () have an absorption spectrum at the edge of the human visible spectrum, either at the UV edge or IR edge, which provides an optical density that is generally imperceptible to humans, but which can be detected by an image capture device (). The crosstalk of visible optical absorption provided by these materials is largely masked by the presence of visible colorant(s) (), with only small color differences between areas with and without the spectral edge markers (). The image capture device () has a visible spectral response that extends into a spectral region just outside the visible spectrum where the spectral edge marker absorption occurs, and can be operated to detect the hidden data.

Spectral edge marking for steganography or watermarking

A method of using an image capture device to identify range information for objects in a scene includes providing an image capture device having an image sensor, a coded aperture having circular symmetry, and a lens; storing in a memory a set of blur parameters derived from range calibration data; capturing images of the scene having a plurality of objects; producing a set of reference edge images using the blur parameters from the stored set; providing a set of deblurred images using the captured image, the reference edges and each of the blur parameters from the stored set; and using the set of deblurred images to determine the range information for the objects in the scene.

Range measurement using symmetric coded apertures

An imaging apparatus with adjustable imaging plane, the apparatus having mechanical, electronic or optical devices to adjust the position and the orientation of the imaging plane, which successively captures a plurality of images while adjusting the imaging plane, and a method to integrate the captured images to a single high-resolution image by exploration of the mutual information not available in a single image, such as the sub-pixel observations due to the spatial misalignment, thus achieving an image resolution higher than the sensor resolution.

Enhancing image resolution by rotation of image plane

In order to analyze a digital video clip to determine candidate frames for subsequent key frame selection, a camera motion sensor is provided in the camera so that information is provided during image capture regarding camera motion including translation of the scene or camera, or scaling of the scene. The sensor includes an accelerometer or a lens motor sensor. A plurality of video segments is formed based on the global motion estimate and each segment is labeled in accordance with a predetermined series of camera motion classes. Thereafter, key frame candidates are extracted from the labeled segments and a confidence score is computed for each candidate by using rules corresponding to each camera motion class and a rule corresponding to object motion.

Analyzing camera captured video for key frames

A method and apparatus for capturing image data from multiple image sensors and generating an output image sequence are disclosed. The multiple image sensors capture data with one or more different characteristics, such as: staggered exposure periods, different length exposure periods, different frame rates, different spatial resolution, different lens systems, and different focal lengths. The data from multiple image sensors is processed and interleaved to generate an improved output motion sequence relative to an output motion sequence generated from an a single equivalent image sensor.

Digital camera using multiple image sensors to provide improved temporal sampling

In an image sequence stabilization method and a camera, a sequence of input digital images are captured. The sequence of input digital images is replicated to provide a corresponding sequence of archival images and a corresponding sequence of display images. The archival image sequence is automatically stabilized to provide a stabilized archival image sequence. The display image sequence is automatically stabilized to provide a stabilized display image sequence. The stabilization methods used for the two sequences are different, although both can be digital.

Image sequence stabilization method and camera having dual path image sequence stabilization

A JPEG2000 compressed image is transcoded to a lower bit-rate or lower resolution, or both, without having to decompress the initial JPEG2000 image and then recompress it to a lower bit-rate and/or resolution. Instead, arithmetic decoding is performed only to the nearest higher bit-rate layer, up to the desired resolution, before performing rate-distortion optimization to produce the transcoded image.

Transcoding a JPEG2000 compressed image

A method for video filtering of an input video sequence by utilizing joint motion and noise estimation includes the steps of: (a) generating a motion-compensated video sequence from the input video sequence and a plurality of estimated motion fields; (b) spatiotemporally filtering the motion compensated video sequence, thereby producing a filtered, motion-compensated video sequence; (c) estimating a standard deviation from the difference between the input video sequence and the filtered, motion-compensated video sequence, thereby producing an estimated standard deviation; (d) estimating a scale factor from the difference between the input video sequence and the motion compensated video sequence; and (e) iterating through steps (a) to (d) using the scale factor previously obtained from step (d) to generate the motion-compensated video sequence in step (a) and using the estimated standard deviation previously obtained from step (c) to perform the filtering in step (b) until the value of the noise level approaches the unknown noise of the input video sequence, whereby the noise level is then characterized by a finally determined scale factor and standard deviation.

Method and system for video filtering with joint motion and noise estimation

Method for transcoding a JPEG2000 compressed image

A method and system for displaying an image, includes steps and means for: storing image data in a manner that enables retrieval of different spatial regions of an image at different fidelities; determining an viewer's point of gaze on a display; retrieving image data for each spatial region of an image at a fidelity that is a decreasing function of the distance of the regions from the point of gaze; and displaying the retrieved image data on the display.

Method and system for displaying an image

A method for authenticating animation, the method comprises the steps of capturing an image; converting the captured image into a wire mesh data for permitting animation of the image; providing movement data, which directs movement of the wire mesh data, and texture data indicating the covering for the wire mesh; electronically transmitting the wire mesh data, texture data and movement data; encrypting the movement data; and electronically transmitting the encryption the movement data for verifying that the animation is unaltered during transmission from its source.

Method for authenticating animation

The horizontal and vertical offset for the M&#xd7;N DCT block boundaries are determined for a decompressed image originally produced by a DCT-based compression system, regardless of the amount of compression and/or cropping that had been applied to the image. The method includes the steps of: a) computing one or more selected DCT coefficients from nonoverlapping, contiguous M&#xd7;N blocks of the decompressed image, beginning at a selected offset; b) computing a coefficient histogram from a set of values for each selected DCT coefficient obtained from the blocks of the decompressed image; c) computing a dispersion metric from each coefficient histogram; d) repeating steps (a) through (c) for a plurality of offsets within an M&#xd7;N block; e) comparing the dispersion metrics corresponding to the plurality of offsets to determine the minimum dispersion coefficient histogram; and f) selecting the offset that corresponds to the minimum dispersion coefficient histogram as the offset for the DCT block boundaries.

Method and system for determining DCT block boundaries

Growing community of inventors

Pittsford, NY, United States of America

Majid Rabbani