Abstract: Systems and methods for block noise detection and filtering are disclosed. One embodiment includes, computing difference magnitudes in pixel values for adjacent pixels in the image. The difference magnitudes can include horizontal difference magnitudes for horizontally adjacent pixels and vertical difference magnitudes for vertically adjacent pixels. One embodiment further includes using normalized sums of the difference magnitudes to determine a set of noise characteristics of the block noise and a set of image characteristics of the image and configuring inputs to the block noise filter using the set of noise and image characteristics.

Abstract: Systems and methods for block noise detection and filtering are disclosed. One embodiment includes, computing difference magnitudes in pixel values for adjacent pixels in the image. The difference magnitudes can include horizontal difference magnitudes for horizontally adjacent pixels and vertical difference magnitudes for vertically adjacent pixels. One embodiment further includes using normalized sums of the difference magnitudes to determine a set of noise characteristics of the block noise and a set of image characteristics of the image and configuring inputs to the block noise filter using the set of noise and image characteristics.

Abstract: System, method, and apparatus for smoothing of edges in images to remove irregularities are disclosed. In one aspect of the present disclosure, a method of image processing includes, identifying an edge in an image having an associated set of edge characteristics, determining the associated set of edge characteristics, and applying a low pass filter to a pixel of the edge based on the associated set of edge characteristics to generate a second image based on the image, wherein the edge in the image is smoothed in the second image. The method further includes generating a third image which is a blend of the original image and the second (edge-smoothed) image based on the associated set of edge characteristics.

Abstract: Systems and methods for block noise detection and filtering are disclosed. One embodiment includes, computing difference magnitudes in pixel values for adjacent pixels in the image. The difference magnitudes can include horizontal difference magnitudes for horizontally adjacent pixels and vertical difference magnitudes for vertically adjacent pixels. One embodiment further includes using normalized sums of the difference magnitudes to determine a set of noise characteristics of the block noise and a set of image characteristics of the image and configuring inputs to the block noise filter using the set of noise and image characteristics.

Abstract: A technique for deinterlacing an interlaced video stream is disclosed. A embodiment of a method includes calculating a pixel using edge detection, calculating a pixel using vertical interpolation, calculating a pixel using weaving, calculating a confidence level, calculating a motion value, blending the edge pixel calculation with the vertical interpolation calculation to generate a first output pixel calculation, the blending being based on the confidence level, and blending the first output pixel calculation with the weaving calculation to generate a second output pixel calculation, the blending being based on the motion value.

Abstract: A method is described for deinterlacing an interlaced video stream. The method includes detecting an occurrence of groups of adjacent fields that are derived from a common original image frame source, and merging field pairs of the interlaced video stream to create a non-interlaced video stream output.

Abstract: A technique for deinterlacing an interlaced video stream is disclosed. A embodiment of a method includes calculating a pixel using edge detection, calculating a pixel using vertical interpolation, calculating a pixel using weaving, calculating a confidence level, calculating a motion value, blending the edge pixel calculation with the vertical interpolation calculation to generate a first output pixel calculation, the blending being based on the confidence level, and blending the first output pixel calculation with the weaving calculation to generate a second output pixel calculation, the blending being based on the motion value.

Abstract: A technique for detecting original scan lines is disclosed. The technique involves receiving a deinterlaced signal with even scan lines and odd scan lines. After the deinterlaced signal is received, a determination is made as to whether the even scan lines or the odd scan lines are the original scan lines. In certain embodiments, an interlaced signal can be generated from the original scan lines. In other embodiments, an optimized deinterlaced signal can be generated using the original scan lines.

Abstract: A technique for deinterlacing an interlaced video stream is disclosed. A method according to the technique can involve calculating a gradient of image intensity and identifying an edge. A bin can be selected that encompasses the edge. An unknown pixel can be calculated by blending known pixel values along the bin boundaries.

Abstract: Systems and methods for block noise detection and filtering are disclosed. One embodiment includes, computing difference magnitudes in pixel values for adjacent pixels in the image. The difference magnitudes can include horizontal difference magnitudes for horizontally adjacent pixels and vertical difference magnitudes for vertically adjacent pixels. One embodiment further includes using normalized sums of the difference magnitudes to determine a set of noise characteristics of the block noise and a set of image characteristics of the image and configuring inputs to the block noise filter using the set of noise and image characteristics.