Abstract: A system and method that adjusts the strength of a de-blocking filter to remove block artifacts in compressed video is disclosed. Block artifacts are associated with the block-based image/video compression techniques. The block artifacts deteriorate the quality of compressed image and video, especially at low bit rates. A de-blocking method estimates the strength of the block artifacts at each block boundary either directly from the MPEG decoder or from a measurement process or both, and adjusts the de-blocking parameters accordingly. An additional block content analysis improves the performance of the overall de-blocking process.

Abstract: A system and method for video frame interpolation are disclosed. In one embodiment, the method comprises receiving first motion estimation data representing estimated motion of blocks between a first frame and a second frame, receiving second motion estimation data representing estimated motion of blocks between the second frame and a third frame, determining whether an area in an interpolated frame between the first and second frame is an occlusion area based at least in part on the first and second motion estimation data, and estimating characteristics of pixels of the area based in part on the determination.

Abstract: An image signal processing unit and an image signal processing method thereof. An image signal processing unit estimates motion characteristics of an input image, and adjusts a phase of an interpolation frame according to the motion characteristics when converting a frame rate. Accordingly, linearity can be maintained according to the motion characteristics of an input image, and the frame rate can be converted without generating noise such as halo artifacts.

Abstract: Embodiments include systems and methods for interpolating frames. In one embodiment, a system and method provides reduced halo and consequently a higher degree of accuracy/fidelity. In one embodiment, a method of video frame interpolation includes receiving forward and backward motion estimation data based on a first video frame and a second, subsequent, video frame. Each block in a plurality of blocks of pixels in an intermediate frame between the first and second frames is classified according to measures of covering and uncovering associated with the forward and backward motion estimation data. A block to be constructed is estimated based on the classification results of proximal ones of the plurality of blocks to the block to be constructed.

Abstract: A method for detecting a pattern in an image includes defining a set of pixel values in an image using a window and calculating a Fourier transform of the pixel values. In one embodiment, the Fourier transform of the pixel values forms a spectrum. The method further comprises analyzing the spectrum of the Fourier transform to find a peak and analyzing the peak to determine whether the peak is indicative of the presence of a pattern in the image.

Abstract: A digital system is provided that combines a digital video camera with television displays, and controlled by a controller module to enhance television performance according to personal television settings, parental controls and energy saving functions, achieved by utilizing the camera and face detection/recognition methods implemented in the controller module.

Abstract: Embodiments include systems and methods for interpolating frames. In one embodiment, a system and method provides reduced halo and consequently a higher degree of accuracy/fidelity. In one embodiment, a method of video frame interpolation includes receiving first motion data based on a first video frame and a second video frame, receiving second motion data based on the second video frame and a third video frame, and estimating a block of an interpolated frame based on the second motion data and the first motion data. In one embodiment, the estimating comprises selectively using the second motion data based on the first motion data.

Abstract: A suppression method that provides adaptive (i.e., selective) processing of an input picture to generate an enhanced output picture with ringing-like areas of the input picture suppressed. For each window in the input picture, if the window is detected as around a ringing-like area in the picture, then the output pixel for the position of the window comprises the low-pass filtered (i.e., smoothed) pixel in the input picture. If the window is not detected as around a ringing-like area, then the output pixel for the position of the window comprises essentially the unchanged window in the input picture. No blurring is introduced in areas where ringing-like patterns are not detected. The output picture is an enhanced version of the input picture comprising portions of the input picture where ringing-like patterns were not detected, and portions of the input picture with suppressed (i.e., smoothed) ringing-like patterns where detected.

Abstract: A system and method for frame rate conversion are disclosed. In one embodiment, the method comprises receiving, at the first device from a second device, input video having a first frame rate, receiving, at the first device from the second device, motion vector information associated with the input video, determining, at the first device, output video having a second frame rate different from the first frame rate, wherein the output video is based on the input video and the motion vector information, and displaying the output video.

Abstract: The present disclosure provides systems and methods for detecting and interpolating still pixels. In certain embodiments, the systems and methods establish a still pixel level for each still pixel, and using that still pixel level, provide an interpolation procedure for determining the pixel value of a selected pixel at a frame a distance ? from frame F(t?1). Disclosed embodiments are capable of providing motion compensated interpolation results for a wide variety of circumstances, including cases where the endpoints of the motion vector of a selected pixel to be interpolated vary between substantially still and not still, as well as cases where mixtures of temporal and motion compensation interpolations are necessary. Still pixel candidates may be refined in a process where pixels that may be properly handled by standard motion compensation interpolation techniques are eliminated.

Abstract: A method of operation of a display system includes: receiving an input image having input pixels; assigning a pixel information for the input pixels corresponding to a semantic category; detecting input background pixels from the input pixels with the pixel information; identifying input foreground pixels from the input pixels with the background pixels; assigning a pixel depth to the input background pixels and input foreground pixels; generating a depth map with the input background pixels and the input foreground pixels; and generating a processed image from the input image with the depth map for displaying on a device.

Abstract: A method of operation of a display system includes: receiving a current input image with current input pixels; identifying an input object, having input object pixels, based on differences in characteristics of the current input pixels; calculating an object pixel depth for the input object pixels from an image depth map of the current input image based on a weighted average of depth candidates; and generating a processed image, having a perceived depth, from the current input image with the image depth map and the object pixel depth for displaying on a device.

Abstract: A method of operation of a three-dimensional display system includes: calculating an edge pixel image from a source image; generating a line histogram from the edge pixel image by applying a transform; calculating a candidate line from the line histogram meeting or exceeding a line category threshold for a horizontal line category, a vertical line category, a diagonal line category, or a combination thereof; calculating a vanishing point on the candidate line; and generating a depth map for the vanishing point for displaying the source image on a first device.

Abstract: A method of operation of a depth estimation system includes: calculating focus measures for positions on a two-dimensional image; generating a depth map for the two-dimensional image based on fitting the focus measure through a Gaussian function; generating a three-dimensional image from the depth map and the two-dimensional image; and processing the three-dimensional image on a storage unit for displaying on a device.

Abstract: A system and method for still object detection in digital video data based on normalized cross correlation are disclosed. One embodiment of the method includes providing video data including a sequence of frames. A pair of consecutive frames are selected from the sequence of frames. A pair of groups of pixels are selected from the pair of consecutive frames. The groups are at corresponding positions on the pair of consecutive frames. The video data includes pixel data for each of the pixels. A normalized cross correlation (NCC) operation is conducted on the pixel data of the selected pair of groups of pixels, thereby generating an NCC value. It is determined whether the NCC value is within a predetermined range, thereby providing whether the groups of pixels displays at least a portion of a still object.

Abstract: A method of processing video data includes: receiving a first video frame with first blocks of pixels associated with a known motion vector and a second video frame with second blocks of pixels, the second blocks corresponding to the first blocks, and uncovered blocks adjacent to the first frame boundary not corresponding to the first blocks in the first video frame; determining a first block for each line segment in the second video frame corresponding to a block in the first video frame, wherein the first block has the known motion vector from the first video frame; and assigning a motion vector for at least one of the line segments in the second video frame to the uncovered blocks in the line segment of the second video frame between first block and the first frame boundary.

Abstract: A system and method of reducing noise are disclosed. In one embodiment a system comprises an input configured to receive an input image, a filter configured to filter the input image to generate a filtered image, a weight generator configured to generate one or more edge weights related to at least one edge of the input image, a mixer configured to generate an output image based on the input image, the filtered image, and at least one of the edge weights, and an output configured to output the output image.

Abstract: An image processing system implements recursive 3D super precision for processing smoothly changing video image areas by performing temporal noise reduction and then 2D super precision. The temporal noise reduction is applied to two frames, one being the current input low precision frame, and the other being the previous higher precision frame from memory. The 2D super precision is applied to the noise reduced frame to output a high precision frame which is also saved into memory for processing the next incoming frame. The input frame has a limited bit depth while the output image has an increased bit depth.

Abstract: A method and a system is provided for deinterlacing interlaced video containing an interlaced image field f including scan lines of multiple pixels. Such deinterlacing involves detecting the one or more edge directions in the image field f using principal component analysis (PCA), and performing spatial interpolation to reconstruct a missing pixel value in the image field f substantially along each of the one or more detected edge directions.

Abstract: System and methods for the detection of progressive pulldown in a video sequence are provided. The method comprises calculating a difference between temporally adjacent frames in the video sequence, generating a pattern based upon these differences, and comparing the generated pattern against patterns understood for known progressive film modes in order to determine if the video sequence comprises a known progressive film mode. In one embodiment, the pattern may be adjusted to account for uncertainty in assigning values to the pattern, reducing the likelihood of false detections. In another advantage, confidence metrics are built into the method in order to further reduce the incidence of false detections.