Abstract: An electronic device configured for defect detection is described. The electronic device includes a processor and instructions stored in memory that is in electronic communication with the processor. The electronic device performs background suppression on the image data based on a transform of the image data to obtain a score map. The electronic device also applies thresholding to the score map to generate a detection mask. The thresholding comprises bi-thresholding. The electronic device additionally detects any defects based on the detection mask. The electronic device further indicates any defects.

Abstract: A system for image processing includes determining edge pixels of a model image using an edge based technique and determining an angular orientation for each the edge pixels of the model image. The system determines a histogram of gradient orientations based upon the angular orientations of the model image. The system determining edge pixels of an input image using an edge based technique and determining an angular orientation for each of the edge pixels of the input image. The system determines a histogram of gradient orientations based upon the angular orientations of the input image. The system compares the histogram of gradient orientations of the model image with the histogram of gradient orientations of the input image to determine candidate locations of an object within the input image.

Abstract: A segmentation description scheme for video material that includes references to segments of video contained in different programs. The segmentation description scheme may also interact with a presentation device to present the referenced segments to a user contiguously, without first storing the segments respectively referenced from the different programs.

Abstract: A system for image processing that matches a model image with an input image. The matching process includes using a feature location index for the model image.

Abstract: A method for image processing includes determining edge pixels of a model image and determining features for the edge pixels of the model image. The image processing includes determining edge pixels of an input image and determining features for the edge pixels of the input image. The system matches the features of the model image with the features of the input image to determine candidate locations of an object within the input image.

Abstract: A method for image processing that includes determining edge pixels of a model image using an edge based technique, and an angular orientation for each of the edge pixels of the model image. The method determines a lower spatial resolution model image based upon the model image and determining respective angular orientations for the lower spatial resolution model image. The method determines edge pixels of an input image using an edge based technique, and an angular orientation for each of the edge pixels of the input image. The method determines a lower spatial resolution input image based upon the input image and determining respective angular orientations for the lower spatial resolution input image. The method matches the lower spatial resolution model image with the lower spatial resolution input image to determine candidate locations of an object within the input image and based upon the candidate locations matching the input image with the model image.

Abstract: A system for determining a high resolution image includes receiving a low resolution image and determining a vector of a patch of the low resolution image based upon a low resolution dictionary. The system includes determining a high resolution patch based upon a high resolution dictionary and the vector and determining the high resolution image based upon the high resolution patch.

Abstract: An electronic device configured for defect detection is described. The electronic device includes a processor and instructions stored in memory that is in electronic communication with the processor. The electronic device performs background suppression on the image data based on a transform of the image data to obtain a score map. The electronic device also applies thresholding to the score map to generate a detection mask. The thresholding comprises bi-thresholding. The electronic device additionally detects any defects based on the detection mask. The electronic device further indicates any defects.

Abstract: A method for interpolation includes receiving an input image having a plurality of pixels. The edge direction proximate a first pixel of the input image is estimated using a first technique from a plurality of discrete potential directions. An edge direction is selected based upon the estimating the edge direction proximate the first pixel of the input image using a second technique. The pixels proximate the first pixel are interpolated based upon the selected edge direction. The pixels proximate the first pixel are interpolated based upon another technique. An output image is determined.

Abstract: A system for image processing includes determining edge pixels of a model image using an edge based technique, and an angular orientation for each of the edge pixels of the model image. The system determines a lower spatial resolution model image based upon the model image and determining respective angular orientations for the lower spatial resolution model image, and determines edge pixels of an input image using an edge based technique, and an angular orientation for each of the edge pixels of the input image. The system determines a lower spatial resolution input image based upon the input image and determining respective angular orientations for the lower spatial resolution input image, and matches the lower spatial resolution model image with the lower spatial resolution input image to determine candidate locations of an object within the image and based upon the candidate locations matching the input image with the model image.

Abstract: A method for multi-scale spatio-temporal steering kernel regression may include repeatedly spatially downsampling input video data, thereby obtaining spatially downsampled video data at a coarsest spatial resolution scale. The spatially downsampled video data at the coarsest spatial resolution scale may be temporally upscaled to generate an estimate of temporally upscaled video data at the coarsest spatial resolution scale. The temporal upscaling may be achieved using spatio-temporal steering kernel regression. Estimates of the temporally upscaled video data may be repeatedly spatially upscaled to generate an estimate of the temporally upscaled video data at the original spatial resolution. The spatial upscaling may be achieved using spatio-temporal steering kernel regression.

Abstract: A transmission system suitable for video where a sender encodes video for transmission to a receiver at an adjustable date rate. The data rate may be adjusted using a delay constraint that constrains the expected delay of transmitted packets. The expected delay may be measured from a time that a transmitter encodes a packet to a time that a receiver decodes a packet.

Abstract: A method for reducing noise in an image from an image capture device includes filter the image using both an offset fixed pattern noise filter and a gain fixed pattern noise filter. Thereafter, the image is filtered using a remnant fixed pattern noise filter to reduce remnant fixed pattern noise.

Abstract: A method for reducing noise in an image from an image capture device includes filter the image using both an offset fixed pattern noise filter and a gain fixed pattern noise filter. Thereafter, the image is filtered using a remnant fixed pattern noise filter to reduce remnant fixed pattern noise.

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

Abstract: A method for classification of samples comprising providing a trained statistical model based upon a set of initial samples. Receiving a set of first samples and training a first statistical model base upon the first set of samples, where the first statistical model is of the same class as the trained statistical model. Receiving a set of second samples and training a second statistical model base upon the second set of samples, where the second statistical model is of the same class as the trained statistical model. The trained statistical model, the first statistical model, and the second statistical model, being independent of each other and collectively used to classify another sample.

Abstract: A method for video processing based on motion-aligned spatio-temporal steering kernel regression may include estimating local spatio-temporal steering parameters at pixels in input video data. The method may also include using the local spatio-temporal steering parameters to apply motion-aligned spatio-temporal steering kernel regression to the input video data to perform at least one of upscaling and noise smoothing.

Abstract: Embodiments of the present invention comprise systems and methods for: authorizing the transmission of audiovisual data based on an iterative changing bit budget, where the bit budget may be based on a value of a total size of the set of Network Abstraction Layer units and a value of an initial size of the group of frames; and determining a bit budget remainder and an adjusted bit budget remainder.

Abstract: A method for adaptive spatio-temporal filtering is disclosed. Local motion vectors between a current video frame and other nearby video frames are determined. Local motion-aligned temporal confidence parameters are determined. Local spatial orientation parameters are determined. The local motion vectors, the local motion-aligned temporal confidence parameters, and the local spatial orientation parameters are used to adaptively determine spatio-temporal kernel weights. The spatio-temporal kernel weights are used to perform spatio-temporal filtering on input video data.

Abstract: A system for producing a motion vector field for a current frame, where the system includes an estimator that selects an initial motion vector from a set of candidate motion vectors and a refiner that refines the initial motion vector.