摘要:
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.
摘要:
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.
摘要:
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.
摘要:
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.
摘要:
A method, system, and computer-readable storage medium are disclosed for generating a location-weighted mask based on a color model comprising spatial dimensions. In one embodiment, a selection of at least one pixel in an input image is received, wherein the selection of the at least one pixel comprises a color and a location within the input image. A color model may be determined based on the color and the location of the at least one pixel, wherein the color model comprises one or more truncated Gaussian functions. A mask may be generated based on the color model. The mask may indicate a degree of membership in the mask for each pixel in the input image as a function of a similarity in color to the at least one pixel in the selection and a proximity to the location of the at least one pixel in the selection.
摘要:
A system and method for expansion and reduction of images uses an absolute value associated with each pixel of an input image (e.g., a color and/or intensity value) to determine a respective energy value for each pixel. For example, a given color or range of colors (e.g., skin tones, or other high-priority colors) may be assigned higher energy values than other colors and/or color ranges, and may be protected during image reduction and/or expansion. These energy values may be used to determine a cost associated with various seams of the image, which may represent the priority of the seams in the image. One or more low-cost seams may be identified for removal or replication to produce a resized image. The methods may be used in conjunction with an automated skin tone detector or a user interface that allows selection of one or more high priority colors or color ranges.
摘要:
Systems, methods, and computer-readable storage media for automatically detecting skin tones in an input image are disclosed. An initial skin tone mask for the image may be created dependent on a general skin tone model. An upper threshold and/or a lower threshold may be applied to the initial skin tone mask to identify pixels most likely to be skin pixels and least likely to be skin pixels, respectively. These pixels may be used to produce an image-specific skin tone model, including one or more truncated Gaussian models for skin pixels and/or non-skin pixels defined in a three-dimensional color space. The image-specific skin tone model may be applied to the image to generate a final skin tone mask. Skin tone detection may be automatically or selectively performed in conjunction with image editing or image feature identification operations to target or exclude skin pixels or non-skin pixels during execution of the operations.
摘要:
A method, system, and computer-readable storage medium are disclosed for generating a mask based on a color model. In one embodiment, a selection of at least one color in an input image is received. A color model may be determined based on the selection of the at least one color, wherein the color model comprises one or more truncated Gaussian functions. A mask may be generated based on the color model. The mask may comprise a respective value indicating a degree of membership in the mask for each of the plurality of pixels in the input image, wherein the degree of membership in the mask is a function of a similarity in color to the selection.
摘要:
A system and method for expansion and reduction of images uses an absolute value associated with each pixel of an input image (e.g., a color and/or intensity value) to determine a respective energy value for each pixel. For example, a given color or range of colors (e.g., skin tones, or other high-priority colors) may be assigned higher energy values than other colors and/or color ranges, and may be protected during image reduction and/or expansion. These energy values may be used to determine a cost associated with various seams of the image, which may represent the priority of the seams in the image. One or more low-cost seams may be identified for removal or replication to produce a resized image. The methods may be used in conjunction with an automated skin tone detector or a user interface that allows selection of one or more high priority colors or color ranges.
摘要:
A sharp frame and a blurred frame are detected from among a plurality of frames. A blur kernel is estimated. The blur kernel represents a motion-transform between the sharp frame and the blurred frame. Using the blur kernel, a static region measure for the sharp frame and the blurred frame is estimated. A de-blurred frame is generated by replacing one or more pixels of the blurred frame as indicated by the static region measure.