Abstract: Embodiments of the present invention provide systems, methods, and computer storage media directed towards automatic selection of regions for blur kernel estimation. In one embodiment, a process divides a blurred image into a regions. From these regions a first region and a second region can be selected based on a number of edge orientations within the selected regions. A first blur kernel can then be estimated based on the first region and a second blur kernel can be estimated for the second region. The first and second blur kernel can then be utilized to respectively deblur a first and second portion of the image to produce a deblurred image. Other embodiments may be described and/or claimed.

Abstract: Embodiments of the present invention provide systems, methods, and computer storage media directed towards automatic selection of regions for blur kernel estimation. In one embodiment, a process divides a blurred image into a regions. From these regions a first region and a second region can be selected based on a number of edge orientations within the selected regions. A first blur kernel can then be estimated based on the first region and a second blur kernel can be estimated for the second region. The first and second blur kernel can then be utilized to respectively deblur a first and second portion of the image to produce a deblurred image. Other embodiments may be described and/or claimed.

Abstract: Content creation and licensing control techniques are described. In a first example, a content creation service is configured to support content creation using an image along with functionality to locate the image or a similar image that is available for licensing. In another example, previews of images are used to generate different versions of content along with an option to license images previewed in an approved version of the content. In a further example, fingerprints are used to locate images used as part of content creation by a content creation service without leaving a context of the service. In yet another example, location of licensable versions of images is based at least in part on identification of a watermark included as part of an image. In an additional example, an image itself is used as a basis to locate other images available for licensing by a content sharing service.

Abstract: Content creation and licensing control techniques are described. In a first example, a content creation service is configured to support content creation using an image along with functionality to locate the image or a similar image that is available for licensing. In another example, previews of images are used to generate different versions of content along with an option to license images previewed in an approved version of the content. In a further example, fingerprints are used to locate images used as part of content creation by a content creation service without leaving a context of the service. In yet another example, location of licensable versions of images is based at least in part on identification of a watermark included as part of an image. In an additional example, an image itself is used as a basis to locate other images available for licensing by a content sharing service.

Abstract: Image search persona techniques and systems are described. In one or more implementations, a digital medium environment is described for controlling image searches by one or more computing devices. An image search request and an indication of one or more personas of one or more respective users associated with the image search request is received by the one or more computing devices. The one or more personas specify characteristics of the one or more respective users themselves. A plurality of images are obtained by the one or more computing devices based on the image search request. The plurality of images are filtered by the one or more computing devices based on the one or more personas and a search result is generated by the one or more computing devices from the filtered plurality of images.

Abstract: Content creation and licensing control techniques are described. In a first example, a content creation service is configured to support content creation using an image along with functionality to locate the image or a similar image that is available for licensing. In another example, previews of images are used to generate different versions of content along with an option to license images previewed in an approved version of the content. In a further example, fingerprints are used to locate images used as part of content creation by a content creation service without leaving a context of the service. In yet another example, location of licensable versions of images is based at least in part on identification of a watermark included as part of an image. In an additional example, an image itself is used as a basis to locate other images available for licensing by a content sharing service.

Abstract: Content creation suggestion techniques are described. In one or more implementations, techniques are implemented to generate suggestions that are usable to guide creative professionals in the creation of content such as images, video, sound, multimedia, and so forth. A variety of techniques are usable to generate suggestions for the content professionals. In a first such example, suggestions are based on shared characteristics of images obtained by users of a content sharing service, e.g., licensed by the users. In another example, suggestions are generated by the content sharing service based on keywords used to locate the images. In a further example, suggestions are generated based on data described communications performed using social network services. In yet another example, recognition of failure of search is used to generate suggestions. A variety of other examples are also contemplated and described herein.

Abstract: Usage based content search result techniques are described. In one or more implementations, a digital medium environment controls image searches and availability by one or more computing devices. A search is performed by the one or more computing devices to locate images made available via a network by a content sharing service responsive to one or more inputs received from a user. A search result is configured by the one or more computing devices that includes the plurality of images based at least in part on an amount of usage of respective said images by other users of the content sharing service. Output of the search result is controlled via a user interface by the one or more computing devices to the user of the content sharing service.

Abstract: Content creation suggestion techniques are described. In one or more implementations, techniques are implemented to generate suggestions that are usable to guide creative professionals in the creation of content such as images, video, sound, multimedia, and so forth. A variety of techniques are usable to generate suggestions for the content professionals. In a first such example, suggestions are based on shared characteristics of images obtained by users of a content sharing service, e.g., licensed by the users. In another example, suggestions are generated by the content sharing service based on keywords used to locate the images. In a further example, suggestions are generated based on data described communications performed using social network services. In yet another example, recognition of failure of search is used to generate suggestions. A variety of other examples are also contemplated and described herein.

Abstract: Content creation and licensing control techniques are described. In a first example, a content creation service is configured to support content creation using an image along with functionality to locate the image or a similar image that is available for licensing. In another example, previews of images are used to generate different versions of content along with an option to license images previewed in an approved version of the content. In a further example, fingerprints are used to locate images used as part of content creation by a content creation service without leaving a context of the service. In yet another example, location of licensable versions of images is based at least in part on identification of a watermark included as part of an image. In an additional example, an image itself is used as a basis to locate other images available for licensing by a content sharing service.

Abstract: A computer-implemented method and apparatus are described for deblurring an image. The method may include accessing the image that has at least one blurred region and, automatically, without user input, determining a first value for a first size for a blur kernel for the at least one blurred region. Thereafter, automatically, without user input, a second value for a second size for the blur kernel is determined for the at least one blurred region. A suggested size for the blur kernel is then determined based on the first value and the second value.

Abstract: A computer-implemented method and system are described for deblurring an image. The method may include accessing an image having a first blurred region and a second blurred region, and generating a first blur kernel for the first blurred region and a second blur kernel for the second blurred region. Thereafter, the first blur kernel is positioned with respect to the first blurred region, and the second blur kernel is positioned with respect to the second blurred region based on the position of the first blur kernel. The image is then deblurred by deconvolving the first blurred region with the first blur kernel, and deconvolving the second blurred region with the second blur kernel.

Abstract: Embodiments of the present invention provide systems, methods, and computer storage media directed towards automatic selection of regions for blur kernel estimation. In one embodiment, a process divides a blurred image into a regions. From these regions a first region and a second region can be selected based on a number of edge orientations within the selected regions. A first blur kernel can then be estimated based on the first region and a second blur kernel can be estimated for the second region. The first and second blur kernel can then be utilized to respectively deblur a first and second portion of the image to produce a deblurred image. Other embodiments may be described and/or claimed.

Abstract: Methods, apparatus, and computer-readable storage media for tone mapping High Dynamic Range (HDR) images. An input HDR image is separated into luminance and color. Luminance is processed to obtain a base layer and a detail layer. The base layer is compressed according to a non-linear remapping function to reduce the dynamic range, and the detail layer is adjusted. The layers are combined to generate output luminance, and the output luminance and color are combined to generate an output image. A base layer compression technique may be used that analyzes the details and compresses the base layer accordingly to provide space at the top of the intensity scale where the details are displayed to thus generate output images that are visually better than images generated using conventional techniques. User interface elements may be provided via which a user may control one or more parameters of the tone mapping method.

Abstract: A computer-implemented method and apparatus are described for deblurring an image. The method may include accessing the image that has at least one blurred region and, automatically, without user input, determining a first value for a first size for a blur kernel for the at least one blurred region. Thereafter, automatically, without user input, a second value for a second size for the blur kernel is determined for the at least one blurred region. A suggested size for the blur kernel is then determined based on the first value and the second value.

Abstract: A computer-implemented method and apparatus are described for automatically selecting a region in a blurred image for blur kernel estimation. The method may include accessing a blurred image and defining a size for each of a plurality of regions in the image. Thereafter, metrics for at least two of the plurality of regions are determined, wherein the metrics are based on a number of edge orientations within each region. A region is selected from the plurality of regions based on the determined metrics, and a blur kernel for deblurring the blurred image is then estimated for the selected region. The blurred image is then deblurred using the blur kernel.

Abstract: A computer-implemented method and apparatus are described for deblurring an image. The method may include accessing the image that has at least one blurred region and, automatically, without user input, determining a first value for a first size for a blur kernel for the at least one blurred region. Thereafter, automatically, without user input, a second value for a second size for the blur kernel is determined for the at least one blurred region. A suggested size for the blur kernel is then determined based on the first value and the second value.

Abstract: Techniques are disclosed relating to modifying an automatically predicted adjustment. In one embodiment, the automatically predicted adjustment may be adjusted, for example, based on a rule. The automatically predicted adjustment may be based on a machine learning prediction. A new image may be globally adjusted based on the modified automatically predicted adjustment.

Abstract: A computer-implemented method and system are described for deblurring an image. The method may include accessing an image having a first blurred region and a second blurred region, and generating a first blur kernel for the first blurred region and a second blur kernel for the second blurred region. Thereafter, the first blur kernel is positioned with respect to the first blurred region, and the second blur kernel is positioned with respect to the second blurred region based on the position of the first blur kernel. The image is then deblurred by deconvolving the first blurred region with the first blur kernel, and deconvolving the second blurred region with the second blur kernel.

Abstract: Methods, apparatus, and computer-readable storage media for tone mapping High Dynamic Range (HDR) images. The HDR image is separated into luminance and color. Luminance is processed according to the parameters to obtain a base layer and a detail layer. The base layer is compressed into a lower dynamic range and the detail layer is adjusted according to the parameters. The compressed base layer, the detail layer, and the color component may be output as separate layers, and various image processing tools and techniques may be applied to the component layers separately to modify the layer(s). One or more tone-mapped images may be generated by merging the modified layers. Thus, each layer of the tone-mapped image may be processed separately using various image processing tools or techniques to modify the output of the tone mapping technique in a wide variety of ways.