Abstract: A method for correcting defects in one or more frames of motion picture film, the method includes the steps of generating an image that includes an infrared channel and one or more color channels; providing an infrared unbuilding model that includes at least one non-linear component that accounts for cross-talk between the one or more color channels and the infrared channel; providing one or more parameters for the infrared unbuilding model; and applying the infrared unbuilding model parameters to the infrared unbuilding model to remove cross-talk between the one or more color channels and the infrared channel to generate an independent infrared channel that is free or substantially free of color channel content.

Abstract: A method of adjusting exposure of a digital camera based on range information, including a digital camera capturing a first digital image at a selected exposure of a scene having objects; providing range information having two or more range values indicating the distance from the digital camera to objects in the scene; using the range information and pixel values of the captured digital image to determine an exposure adjustment amount for the selected exposure; and applying the exposure adjustment amount to the digital image to produce a second digital image with adjusted exposure.

Abstract: 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.

Abstract: A method for correcting defects in one or more frames of motion picture film, the method includes the steps of generating an image that includes an infrared channel and one or more color channels; providing an infrared unbuilding model that includes at least one non-linear component that accounts for cross-talk between the one or more color channels and the infrared channel; providing one or more parameters for the infrared unbuilding model; and applying the infrared unbuilding model parameters to the infrared unbuilding model to remove cross-talk between the one or more color channels and the infrared channel to generate an independent infrared channel that is free or substantially free of color channel content.

Abstract: 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 approach

Abstract: A method for synthesizing noise in a digital image comprises the steps of (a) estimating noise statistics based on a set of spatial autocorrelation coefficients and a set of spectral correlation coefficients that correspond to the color channels of the image, where at least one of the spatial autocorrelation coefficients is weighted by at least one of the spectral correlation coefficients, thereby providing a weighted set of autocorrelation coefficients, and where a set of filter coefficients is obtained from the weighted set of autocorrelation coefficients; and (b) synthesizing a synthetic texture by using the filter coefficients to filter a random noise field in each of the color channels, thereby producing output noise fields in each of the color channels that replicate a synthetic texture, e.g., a desired grain appearance, when combined into the digital image.

Abstract: A method of adjusting exposure of a digital camera based on range information, including a digital camera capturing a first digital image at a selected exposure of a scene having objects; providing range information having two or more range values indicating the distance from the digital camera to objects in the scene; using the range information and pixel values of the captured digital image to determine an exposure adjustment amount for the selected exposure; and applying the exposure adjustment amount to the digital image to produce a second digital image with adjusted exposure.

Abstract: A method of processing a digital image of a scene to locate a planar surface in the digital image, includes providing a range information including two or more range values indicating the distance of objects in the scene from a known reference frame; and using a planar model and the range information to locate one or more planar surfaces in the digital image.

Abstract: A method of detecting an object of interest having a known size in a digital image, includes providing a range information including two or more range values indicating the distance of objects in the scene from a known reference frame; detecting a candidate object of interest in the image; determining range values corresponding to the candidate object of interest and using these range values and the known size of the object of interest to classify the candidate object of interest.

Abstract: A method for extracting a watermark signal contained in a watermarked digital image sequence having two or more frames, including the steps of estimating correspondences between one or more pairs of frames in the watermarked digital image sequence; computing a displaced frame difference for one or more frames in the watermarked digital image sequence using the correspondences; and extracting the watermark signal from one or more displaced frame differences.

Abstract: 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.

Abstract: A method for digitally processing motion image signals comprises the steps of: (a) obtaining digital motion image signals that originated from a sequence of motion picture frames; (b) using a frame averaging technique to reduce noise in the digital motion image signals, thereby producing noise-processed motion image signals; and (c) producing output digital motion image signals by sharpening the noise-processed motion image signals with a sharpening filter designed in the spatial domain with a 2D kernel that increases the noise in order to provide a desired grain response.

Abstract: A method is described for processing motion picture scene data through a process in which the scene data is initially acquired from a film or an electronic camera and ultimately projected onto a screen, wherein image losses potentially occur during distribution and projection stages of the process. The method includes the steps of: (a) representing the scene data in a non-linear space; and (b) compensating for the image losses associated with the distribution and projection stages at a point in the process before they occur by converting the scene data into an intermediate space representing the space in which the losses occur and filtering the scene data in the intermediate space to compensate the scene data for the losses.

Abstract: A method for video filtering of an input video sequence by utilizing joint motion and noise estimation comprises 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 approac

Abstract: A method for determining the noise level, as characterized by the standard deviation, of an input video sequence corrupted by unknown noise comprises the steps of: (a) spatiotemporally filtering the input video sequence, thereby producing a filtered video sequence; (b) estimating a standard deviation from the difference between the input video sequence and the filtered video sequence, thereby producing an estimated standard deviation; and (c) iterating through steps (a) and (b) using the estimated standard deviation previously obtained from step (b) to perform the filtering in step (a) until the value of the noise level approaches the unknown noise, whereby the noise level is then characterized by a finally determined standard deviation.

Abstract: A method for synthesizing noise in a digital image comprises the steps of (a) estimating noise statistics based on a set of spatial autocorrelation coefficients and a set of spectral correlation coefficients that correspond to the color channels of the image, where at least one of the spatial autocorrelation coefficients is weighted by at least one of the spectral correlation coefficients, thereby providing a weighted set of autocorrelation coefficients, and where a set of filter coefficients is obtained from the weighted set of autocorrelation coefficients; and (b) synthesizing a synthetic texture by using the filter coefficients to filter a random noise field in each of the color channels, thereby producing output noise fields in each of the color channels that replicate a synthetic texture, e.g., a desired grain appearance, when combined into the digital image.

Abstract: A method is described for processing motion picture scene data through a process in which the scene data is initially acquired from a film or an electronic camera and ultimately projected onto a screen, wherein image losses potentially occur during distribution and projection stages of the process. The method includes the steps of: (a) representing the scene data in a non-linear space; and (b) compensating for the image losses associated with the distribution and projection stages at a point in the process before they occur by converting the scene data into an intermediate space representing the space in which the losses occur and filtering the scene data in the intermediate space to compensate the scene data for the losses.

Abstract: A method for extracting a watermark signal contained in a watermarked digital image sequence having two or more frames, including the steps of estimating correspondences between one or more pairs of frames in the watermarked digital image sequence; computing a displaced frame difference for one or more frames in the watermarked digital image sequence using the correspondences; and extracting the watermark signal from one or more displaced frame differences.

Abstract: A method for digitally processing motion image signals comprises the steps of: (a) obtaining digital motion image signals that originated from a sequence of motion picture frames; (b) using a frame averaging technique to reduce noise in the digital motion image signals, thereby producing noise-processed motion image signals; and (c) producing output digital motion image signals by sharpening the noise-processed motion image signals with a sharpening filter designed in the spatial domain with a 2D kernel that increases the noise in order to provide a desired grain response.