Abstract:
An apparatus for content based anti-aliasing is described herein. The apparatus comprises a detector, corrector, and downscaler. The detector is to detect potential aliased content in an input image, wherein the potentially aliased content occurs at a downscaled version of the input image. The corrector is to apply a correction to a single component of the input image. A downscaler may downscale the corrected input image to an output image according to a scaling factor.
Abstract:
An apparatus for content based anti-aliasing is described herein. The apparatus comprises a detector, corrector, and downscaler. The detector is to detect potential aliased content in an input image, wherein the potentially aliased content occurs at a downscaled version of the input image. The corrector is to apply a correction to a single component of the input image. A downscaler may downscale the corrected input image to an output image according to a scaling factor.
Abstract:
An apparatus for edge aware upscaling is described herein. The apparatus comprises a potential edge detector, a thin-edge detector, a one-directional edge detector, a correlation detector, and a corrector. The potential edge detector identifies potential edge pixels in an input image, and the thin-edge detector detects thin edges in the potential edge pixels of the input image. The one-directional edge detector detects one-directional edges in the potential edge pixels of the input image, and the correlation detector detects strongly correlated edges in the potential edge pixels of the input image. The corrector derives a target output value based on an edge type and classification of a corresponding input pixel as identified by a source map point.
Abstract:
An apparatus for edge aware upscaling is described herein. The apparatus comprises a potential edge detector, a thin-edge detector, a one-directional edge detector, a correlation detector, and a corrector. The potential edge detector identifies potential edge pixels in an input image, and the thin-edge detector detects thin edges in the potential edge pixels of the input image. The one-directional edge detector detects one-directional edges in the potential edge pixels of the input image, and the correlation detector detects strongly correlated edges in the potential edge pixels of the input image. The corrector derives a target output value based on an edge type and classification of a corresponding input pixel as identified by a source map point.
Abstract:
Techniques related to demosaicing for digital image processing are discussed. Such techniques include correcting defective pixels by detecting hot and warm pixels and correcting such detected hot and warm pixels based on neighboring pixels and angle compensation including detecting dominant angles and compensating for such detected angles during demosaicing.