Abstract: Dynamic motion path blur techniques are described. In one or more implementations, paths may be specified to constrain a motion blur effect to be applied to a single image. A variety of different techniques may be employed as part of the motion blur effects, including use of curved blur kernel shapes, use of a mesh representation of blur kernel parameter fields to support real time output of the motion blur effect to an image, use of flash effects, blur kernel positioning to support centered or directional blurring, tapered exposure modeling, and null paths.

Abstract: Dynamic motion path blur techniques are described. In one or more implementations, paths may be specified to constrain a motion blur effect to be applied to a single image. A variety of different techniques may be employed as part of the motion blur effects, including use of curved blur kernel shapes, use of a mesh representation of blur kernel parameter fields to support real time output of the motion blur effect to an image, use of flash effects, blur kernel positioning to support centered or directional blurring, tapered exposure modeling, and null paths.

Abstract: A mesh is a collection of multiple shapes referred to as elements, each of which can share an edge with one or more other elements of the mesh. The mesh is presented to the user on a display, and the user identifies a new element to be added to the mesh. User input is received to manipulate the new element (e.g., move the new element around the display). As the new element is manipulated, various conditions are applied to determine edges of elements existing in the mesh that the new element can be snapped to. Snapping a new element to an edge of an existing element in the mesh refers to adding the new element to the mesh so that the new element and the existing element share the edge. Indications of the edges of existing elements to which the new element can be snapped are provided to the user.

Abstract: Methods and apparatus for manipulating digital images. A warping module is described that enables the manipulation of a surface by selectively deforming portions of the surface while maintaining local rigidity. The user may position multiple control points on a surface to constrain deformation. The user may specify multiple properties (e.g., translation, rotation, depth, and scale) at each control point. A mesh may be overlaid on the surface. The warping module may perform an initialization in which the properties are propagated other vertices in the mesh to generate an initial deformed mesh. The warping module may then perform an iterative optimization operation on the deformed mesh to improve the deformation while retaining local rigidity. Thus, instead of moving every pixel in the surface, the warping module moves or adjusts coordinates of the vertices of the mesh. The surface is then deformed according to the deformed mesh.

Abstract: Methods and apparatus for manipulating digital images. A warping module is described that enables the manipulation of a surface by selectively deforming portions of the surface while maintaining local rigidity. The user may position multiple control points on a surface to constrain deformation. The user may specify multiple properties (e.g., translation, rotation, depth, and scale) at each control point. A mesh may be overlaid on the surface. The warping module may perform an initialization in which the properties are propagated other vertices in the mesh to generate an initial deformed mesh. The warping module may then perform an iterative optimization operation on the deformed mesh to improve the deformation while retaining local rigidity. Thus, instead of moving every pixel in the surface, the warping module moves or adjusts coordinates of the vertices of the mesh. The surface is then deformed according to the deformed mesh.

Abstract: Various embodiments of methods and apparatus for motion deblurring are disclosed. In one embodiment, an estimate of a latent image of a blurred image at a current scale from an estimate of a latent image at a previous coarse scale is generated using an upsampling super-resolution function, and a blur kernel is estimated based on the estimate of the latent image and the blurred image; and are repeated from a course to fine scale. A final image estimate is generated. The generating the final image estimate includes performing a deconvolution of the latent image using the blur kernel and the blurred image.

Abstract: Methods and systems for denoising and artifact removal in image upscaling are disclosed. In one embodiment, a low frequency band image intermediate is obtained from an input image. An upsampled image intermediate is obtained from the input image by upsampling. A result image is estimated, based at least in part on the upsampled image intermediate, the low frequency band image intermediate, and the input image. The input image is of a smaller scale than the result image. The estimating the result image further includes eliminating from the result image noise that is present in the input image.

Abstract: Various embodiments of methods and apparatus for motion deblurring in text images are disclosed. In one embodiment, a threshold-based text prediction for a blurred image is generated. A point spread function for the blurred image is estimated. A result of the threshold-based text prediction function is deconvolved based on the point spread function. The generating, estimating, and deconvolving are iterated at a plurality of scales, and a final deconvolution of a result of the iteratively deconvolving is executed.

Abstract: Methods and systems for image upscaling are disclosed. In one embodiment, a low frequency band image intermediate is obtained from an input image. The input image is upsampled by a scale factor to obtain an upsampled image intermediate. A result image is estimated based at least in part on the upsampled image intermediate, the low frequency band image intermediate, and the input image, wherein the input image is of a smaller scale than the result image.

Abstract: Methods and systems for a regression-based learning model in image upscaling are disclosed. In one embodiment, a set of image patch pairs for each of a set of images is generated. Each of the image patch pairs contains a natural image and a corresponding downscaled lower-resolution image. A regression model based at least in part on the set of image patch pairs is defined. The regression model represents a gradient of a function of the downscaled lower-resolution image. An image is upscaled based at least in part on the regression model.

Abstract: A method, apparatus and computer program product for setting alternate style assignments to menu elements of an application are presented. At least one menu element of an application is selected. An alternate style is assigned to the at least one menu element. The at least one menu elements of the application is displayed, wherein the at least one menu element is presented in the alternate style assigned to the element.

Abstract: Methods and apparatus for manipulating digital images. A warping module is described that enables the manipulation of a surface by selectively deforming portions of the surface while maintaining local rigidity. The user may position multiple control points on a surface to constrain deformation. The user may specify multiple properties (e.g., translation, rotation, depth, and scale) at each control point. A mesh may be overlaid on the surface. The warping module may perform an initialization in which the properties are propagated other vertices in the mesh to generate an initial deformed mesh. The warping module may then perform an iterative optimization operation on the deformed mesh to improve the deformation while retaining local rigidity. Thus, instead of moving every pixel in the surface, the warping module moves or adjusts coordinates of the vertices of the mesh. The surface is then deformed according to the deformed mesh.

Abstract: Various embodiments of methods and apparatus for motion deblurring are disclosed. In one embodiment, an estimate of a latent image of a blurred image at a current scale from an estimate of a latent image at a previous coarse scale is generated using an upsampling super-resolution function, and a blur kernel is estimated based on the estimate of the latent image and the blurred image; and are repeated from a course to fine scale. A final image estimate is generated. The generating the final image estimate includes performing a deconvolution of the latent image using the blur kernel and the blurred image.

Abstract: Various embodiments of methods and apparatus for motion deblurring in text images are disclosed. In one embodiment, a threshold-based text prediction for a blurred image is generated. A point spread function for the blurred image is estimated. A result of the threshold-based text prediction function is deconvolved based on the point spread function. The generating, estimating, and deconvolving are iterated at a plurality of scales, and a final deconvolution of a result of the iteratively deconvolving is executed.

Abstract: Methods and apparatus for generating variable-width border masks for objects in input images. Given an input image and an initial binary selection of an object in the image, a variable-width border mask method may be applied to automatically generate an accurate, variable-width border mask for the object. An initial border mask may be generated. An initial foreground probability map may be generated within the initial border mask using a Gaussian Mixture color modeling technique. A geodesic smoothing technique may be applied to the initial foreground probability map to reduce or remove noise. An optimization technique may be applied to optimize the foreground boundary, and a final variable-width border mask may be generated. The variable-width border mask may be used as input to image matting algorithms to generate an accurate alpha mask of the foreground object selected from the input image.

Abstract: Various embodiments of methods and apparatus for removing unwanted background color from a border region surrounding a foreground object in an image in order to composite the foreground object of the image with a new background image are described. Embodiments of color decontamination for image compositing may accept an image and an alpha matte corresponding to the image as input. In some embodiments, estimated foreground colors are determined for pixels in a border region between the foreground and the background of the input image. In some embodiments, the input image may be created by down-sampling a higher resolution image and pixels with estimated foreground colors may be up-sampled. In some embodiments, a composite image may be created based on the input image, the alpha matte, the estimated foreground colors of pixels in the border region and a new background image.

Abstract: Methods and systems for image upscaling are disclosed. In one embodiment, a low frequency band image intermediate is obtained from an input image. The input image is upsampled by a scale factor to obtain an upsampled image intermediate. A result image is estimated based at least in part on the upsampled image intermediate, the low frequency band image intermediate, and the input image, wherein the input image is of a smaller scale than the result image.

Abstract: Methods and systems for denoising and artifact removal in image upscaling are disclosed. In one embodiment, a low frequency band image intermediate is obtained from an input image. An upsampled image intermediate is obtained from the input image by upsampling. A result image is estimated, based at least in part on the upsampled image intermediate, the low frequency band image intermediate, and the input image. The input image is of a smaller scale than the result image. The estimating the result image further includes eliminating from the result image noise that is present in the input image.

Abstract: Methods and systems for a regression-based learning model in image upscaling are disclosed. In one embodiment, a set of image patch pairs for each of a set of images is generated. Each of the image patch pairs contains a natural image and a corresponding downscaled lower-resolution image. A regression model based at least in part on the set of image patch pairs is defined. The regression model represents a gradient of a function of the downscaled lower-resolution image. An image is upscaled based at least in part on the regression model.

Abstract: A method, system, and computer-readable storage medium are disclosed for editing a digital image with automatic conversion of region modalities. Input comprising an instruction to perform an operation on a first portion of the digital image may be received. The first portion of the digital image may comprise data defined by a first region modality. The operation may be applicable to data defined by a second region modality. In response to receiving the input, the first portion of the digital image may be automatically converted from the first region modality to the second region modality. The operation may be automatically performed on the converted first portion of the digital image (i.e., as defined by the second region modality).