Abstract: Various methods and systems are provided for image processing for multiple cameras. In one embodiment, a method comprises acquiring image frames with a plurality of image frame sources configured with different acquisition settings, processing the image frames based on the different acquisition settings to generate at least one final image frame, and outputting the at least one final image frame. In this way, information from different image frame sources such as cameras may be leveraged to achieve increased frame rates with improved image quality and a desired motion appearance.

Abstract: Various methods and systems are provided for image processing for multiple cameras. In one embodiment, a method comprises acquiring a plurality of image frames from each image frame source of a plurality of image frame sources, each plurality of image frames acquired at a first frame rate, combining the plurality of image frames from each image frame source into a single plurality of image frames with a second frame rate higher than the first frame rate, and outputting the single plurality of image frames as a video. In this way, high-frame-rate video may be obtained with multiple low-frame-rate image frame sources or cameras.

Abstract: Various methods and systems are provided for image processing for multiple cameras. In one embodiment, a method comprises acquiring image frames with a plurality of image frame sources configured with different acquisition settings, processing the image frames based on the different acquisition settings to generate at least one final image frame, and outputting the at least one final image frame. In this way, information from different image frame sources such as cameras may be leveraged to achieve increased frame rates with improved image quality and a desired motion appearance.

Abstract: A method of calibrating a display panel includes making measurements of color components produced by the display panel, receiving an input image signal consisting of one or more pixel represented by input color component values, applying a first non-linear transform to the input color component values of the pixel to produce transformed color component values, wherein the first non-linear transform is either based upon the measurements and the panel design or a ratio of values of color components based upon the measurements, applying a crosstalk correction transform to the transformed color component values to produce crosstalk corrected color component values, applying a second non-linear transform to the crosstalk corrected color component values to produce final color component values, and sending the final color component values to the display panel.

Abstract: A method includes receiving, at a processor, at least one frame of input image data, producing motion vector fields between the frames of input image data, and applying temporal stability to the at least one frame of the input image data to produce noise reduced image data, wherein applying temporal stability comprises separating pixel data into frequency bands.

Abstract: A method of calibrating a display panel including making measurements of color components displayed on the display panel, using the measurements to generate at least two non-linear models for each color component, receiving an input image consisting of one or more pixels represented by input color values, calculating a crosstalk gain for a given value of the color components using the generated non-linear models and the input values of a pixel, applying the crosstalk gain to the color components of the pixel to create crosstalk compensated component values, and displaying an image using the crosstalk compensated component values.

Abstract: A method of encoding a non-linear, color space video signal includes converting the non-linear video signal to a linear video signal, transforming the non-linear signal to produce a transformed non-linear signal, transforming the linear signal to product a transformed linear signal, using the transformed linear signal to determine errors, applying the errors to the non-linear, color space video signal to produce a compensated non-linear color space signal, and encoding the compensated signal.

Abstract: A method of converting an input frame rate of input video frames includes upsampling at least some of the input video frames to produce upsampled frames at a higher frame rate than the input frame rate, applying a filter to combine together multiple frames at a single pixel location, downsampling the upsampled frames to an output frame rate. A method of converting an input frame rate of input video frames includes grouping input video frames together, wherein a number of groups per second is less than a capture frame rate, and interpolating the frames within a group to obtain a desired shutter angle, wherein an average time between frames within a group is less than a time between groups.

Abstract: A method of estimating motion in video display data includes dividing a frame of the video display data into blocks, generating at least two motion models for a current block from motion models of neighboring blocks to the current block, and selecting one of the motion models based upon a similarity of the motion model that minimizes differences between corresponding blocks in reference frames to the current block.

Abstract: A method of producing video data includes receiving, at a processor, a current frame of image data in a stream of frames of image data, dividing a current frame of image data into blocks, identifying a current block and defining a neighborhood of blocks for the current block, generating at least one initial motion vector for each block, using the initial motion vector for current block and an initial motion model to calculate a weight for each initial motion vector in the neighborhood based on a difference between initial motion vector for the current block and the initial motion vector for at least one other block from the current block in the neighborhood and differences in the image data between the current block and the other blocks in the neighborhood, using the weights for each initial motion vector to generate coefficients for a refined motion model, refining the initial motion vector for the current block according to the refined motion model to produce a refined motion vector, using the refined motio

Abstract: A method of adjusting motion in a video sequence, includes performing motion estimation on an original video sequence and producing initial motion vectors and motion statistics, using the motion statistics to determine a level of motion estimation and motion compensation (MEMC) in the video sequence, adjusting a frame interpolation process based upon the level, and producing a frame interpolated video sequence from the original video sequence and the adjusted frame interpolation process.

Abstract: A method of displaying variable rate video data includes receiving a signal from a display indicating that the display is ready to accept a frame of video data, analyzing image content of scenes in the video data, using the image content of scenes in the video data to cluster the scenes into scene types based upon a motion level, adjusting motion estimation and motion compensation to produce a variable output frame rate of the video data not synchronized with an input frame rate, the variable output frame rate based upon the scene type, wherein the variable output frame rate employs interpolated frames, wherein interpolated phases used to form the interpolated frames are determined by the motion level and a phase relationship between the input frames and the display timing, receiving the video data at the variable output frame rate at a display panel, and displaying the video data at the variable output frame rate.

Abstract: A method of performing motion vector correction in a sequence of video frames includes receiving, at a processor, a frame of video frames at a received rate lower than an original frame rate, identifying motion vector candidates for a frame in the sequence of video frames, detecting a cadence of the sequence of video frames using the motion vector candidates, scaling the motion vector candidates according to the cadence to produce scaled motion vector candidates, calculating motion vectors for a frame in the sequence of video frames using the scaled motion vector candidates, and interpolating at least one new frame of video data using the motion vectors.

Abstract: A method includes determining a display backlight level based upon an ambient light level, using image content of incoming image data to adjust the display backlight level based upon image content to produce an image-compensated backlight value, and adjusting pixel values in the image data as needed based upon the image-compensated backlight value.

Abstract: A method of converting three dimensional image data into two dimensional image data, includes identifying at least two vertices of an object to be rendered in a frame of three dimensional image data, calculating a three-dimensional (3D) motion vector for each vertex of the object to be rendered, determining a position of each vertex in a new frame, calculating the motion vectors for a block based upon the vertex position in the new frame and the motion vectors for the vertex, and using the motion vectors for the vertex to render pixels in the new frame.

Abstract: A system can include a memory and a motion vector calculator (MVC) configured to receive a block from the memory, the MVC including an MVC core configured to generate a partial motion vector (MV) for the block, a halo reduction block configured to perform halo reduction on the partial MV, and an MV post-processing block configured to smooth the partial MV and output the smoothed partial MV.

Abstract: A method includes receiving, at a processor, a frame of input image data, generating at least one motion vector field between a first frame of input image data and an adjacent frame of input image data, refining the at least one motion vector field to provide refined motion vectors, temporally filtering a frame of input image data to produce a temporally filtered frame of image data, and generating a frame of interpolated image data using the temporally filtered frame of image data and the refined motion vectors.

Abstract: A method of generating super resolution image data includes receiving original image data of a low resolution at an image processing device, performing motion compensation on the original image data using a current frame of image data and at least one previous frame of image data and at least one future frame of image data as reference frames, generating motion vectors, applying noise reduction to the current frame of image data and the reference frames to produce noise reduced, current frame image data, and generating a current frame of super resolution image data using the noise reduced, current frame image data.

Abstract: A method of developing an image training library includes receiving, at a processor, a set of high resolution image samples at a first resolution, generating a set of low resolution image samples having a second resolution from the set of high resolution images, wherein the second resolution is lower than the first resolution, clustering the low resolution image samples using features in the low resolution images, generating a low resolution dictionary for each cluster, generating sparse coefficients for each sample, and using the sparse coefficients to generate a high resolution dictionary for each cluster.

Abstract: A method of scaling image data, includes receiving image data at a processor in at least two channels, the image data having a first resolution for the a channel and a second, lower resolution for other channels, using known pixel values of the first resolution pixels to generate an interpolation function to be applied to second resolution pixels co-located with a subset of the first resolution pixels, and applying the interpolation function to the second resolution pixels to find the unknown pixel values.