Abstract: A method for the reduction of noise in an image including identifying neighboring pixel values in pixels proximate to a subject pixel; comparing the neighboring pixel values to a preset tolerance range; using neighboring pixel values within the tolerance range to calculate a pixel intensity correction value; and applying the pixel intensity value to the subject pixel.

Abstract: Systems and methods of providing an attractiveness analysis are disclosed. In some embodiments, an electronic analysis platform is configured to obtain image data and curvature data to provide an attractiveness analysis to a user via a physical interface. Curvature data could comprise any data indicative of a curvature of a physical feature or a depiction thereof, including shadow data and pixilation data.

Abstract: A system for determining a high resolution output image that includes receiving a low resolution image having a first resolution and determining an intermediate high resolution image having a second resolution based upon the low resolution image, where the second resolution is greater than the first resolution. The system determines a set of matches between a patch of the intermediate high resolution image and each of a plurality of degraded high resolution images, then selecting a subset of the set of matches and determining a corresponding reside patch for each of the subset of the set of patches. The system modifies the intermediate high resolution image based upon the corresponding reside patches to determine the high resolution output image.

Abstract: An image processing apparatus comprises a storage unit configured to store feature information of a predetermined object, a determination unit configured to detect feature information of an object from an image to be searched and determine a similarity to the feature information of the predetermined object stored in the storage unit, a search unit configured to search a candidate image containing the predetermined object as a result of the determination by the determination unit, and a control unit configured to control, based on attribute information associated with image-shooting conditions, the order in which images are subjected to the determination processing by the determination unit.

Abstract: Cropping boundary simplicity techniques are described. In one or more implementations, multiple candidate croppings of a scene are generated. For each of the candidate croppings, a score is calculated that is indicative of a boundary simplicity for the candidate cropping. To calculate the boundary simplicity, complexity of the scene along a boundary of a respective candidate cropping is measured. The complexity is measured, for instance, using an average gradient, an image edge map, or entropy along the boundary. Values indicative of the complexity may be derived from the measuring. The candidate croppings may then be ranked according to those values. Based on the scores calculated to indicate the boundary simplicity, one or more of the candidate croppings may be chosen e.g., to present the chosen croppings to a user for selection.

Abstract: Disclosed are systems and methods for automatically applying special effects based on media content characteristics. A digital image is obtained and depth information in the digital image is determined. A foreground region and a background region in the digital image are identified based on the depth information. First and second effects are selected from a grouping of effects, where the first effect is applied to at least a portion of the foreground region and the second effect is applied to at least a portion of the background region.

Abstract: A method for the reduction of noise in an image including identifying neighboring pixel values in pixels proximate to a subject pixel; comparing the neighboring pixel values to a preset tolerance range; using neighboring pixel values within the tolerance range to calculate a pixel intensity correction value; and applying the pixel intensity value to the subject pixel.

Abstract: Image cropping suggestion is described. In one or more implementations, multiple croppings of a scene are scored based on parameters that indicate visual characteristics established for visually pleasing croppings. The parameters may include a parameter that indicates composition quality of a candidate cropping, for example. The parameters may also include a parameter that indicates whether content appearing in the scene is preserved and a parameter that indicates simplicity of a boundary of a candidate cropping. Based on the scores, image croppings may be chosen, e.g., to present the chosen image croppings to a user for selection. To choose the croppings, they may be ranked according to the score and chosen such that consecutively ranked croppings are not chosen. Alternately or in addition, image croppings may be chosen that are visually different according to scores which indicate those croppings have different visual characteristics.

Abstract: A method and system to enhance analysis of electrophoretic bands by overlaying only the pixels of interest. The overlaid pixels are superimposed as a layer above, i.e., in the foreground of, the overlaid image, i.e., in the background. A user employs the superimposed pixels for molecular weight determination and is still able to generate densitometry analysis of the remaining pixels in the overlaid image.

Abstract: A system, method, and computer program product are provided for exchanging images. In use, one or more images are received at a server. Additionally, the one or more images are analyzed. Further, image processing code is outputted referencing the one or more images, based on the analysis of the one or more images. Additional systems, methods, and computer program products are also presented.

Abstract: A novel modification to the order statistics filters called the Adaptive Weighted-Local-Difference Order Statistics is shown that will act as a generic framework for the design of adaptive filters suitable for specific signal processing applications. To demonstrate the design of filters using this framework two implementations were defined and evaluated: Edge Orientation Adaptive Weighted-Local-Difference Median Filter (EOAWLDMF) and Luminance-Similarity Adaptive Weighted-Local-Difference Median Filter (LSAWLDMF) for restoration of noisy images.

Abstract: An image registration method for registering images into a coordinate system includes the following steps: (a) performing image normalization on a source image and generating a normalized image; (b) retrieving at least one color-deconvoluted image from color-deconvoluting the source image; (c) determining at least one image feature from the at least one color-deconvoluted image; (d) comparing the at least one image feature of the at least one color-deconvoluted image with a target image, and generating a relative matching structural feature result; and (e) transforming the normalized image into a registered image according to the matching structural feature result.

Abstract: Techniques for assuring the quality of mobile document image captured using a mobile device are provided. These techniques include performing one or more tests to assess the quality of images of documents captured using the mobile device. The tests can be selected based on the type of document that was imaged, the type of mobile application for which the image quality of the mobile image is being assessed, and/or other parameters such as the type of mobile device and/or the characteristics of the camera of the mobile device that was used to capture the image. The image quality assurance techniques can also be implemented on can be implemented on a mobile device and/or on a remote server where the mobile device routes the mobile image to the remote server processing and the test results are be passed from the remote server to the mobile device.

Abstract: Provided is an image processing apparatus and method for adjusting a color image using a depth image. The image processing apparatus may include a color image segmenting unit to segment a color image into a plurality of color segments, using a color layer of the color image, a depth image segmenting unit to segment a depth image into a plurality of depth segments, using a depth layer of the depth image, and a layer boundary adjusting unit to adjust a boundary value of the color layer, using the plurality of color segments and the plurality of depth segments.

Abstract: A method and apparatus for encoding an image, and a method and apparatus for decoding an image are provided. In the image encoding method, an input image may be encoded hierarchically based on a unified image compression format, irrespective of whether the input image corresponds to a two-dimensional (2D) image, a stereo image, or a three-dimensional (3D) image. An encoded bit stream generated through the encoding may be transmitted to the image decoding apparatus.

Abstract: Provision can be made of a high-speed image processing apparatus that eliminates poor visibility in a dotted configuration or a superimposed portion of two streaks upon removing a false image due to statistical noise. That is, provision can be made of a high-speed image processing apparatus capable of outputting a processed image of high visibility in accordance with a shape of a configuration of a subject appearing in an original image upon removing a false image associated with the statistical noise. A band image noise extract generating unit performs image processing by superimposing a band image, an isotropic blur image, and an anisotropic blur image while changing weighting for each pixel in accordance with edge reliability. Such a construction eliminates poor visibility in the dotted configuration or the superimposed portion of two streaks upon removing the false image in the original image.

Abstract: A line segmentation method which starts with determining a first starting point coordinate and generating a list of potential character widths dependent on a maximum character width stored in a database and on characteristics of the portion of the line of text corresponding to the maximum character width. The method determines a second portion of the line of text corresponding to the first starting point coordinate and the first width on the list of potential character widths. On the second portion, a classification method is applied providing a likelihood of error for the first width and a candidate character. The likelihood of error is compared with a first threshold determined by a trade-off between speed and accuracy, and if the likelihood of error corresponding to the first width is lower than the threshold value, the candidate character is selected as the character meaning that a segment is known.

Abstract: Systems, methods, and computer readable media for adjusting the orientation of an image frame and a scene depicted in the image frame are described. In general, techniques are disclosed for analyzing an image with one or more feature detectors to identify features in the image. An alignment or position associated with one or more features identified in the image may be used to determine a proper orientation for the image frame. The image can then be rotated to the proper orientation. It may also be determined if a scene depicted in the image is properly aligned in the rotated image orientation. If not, alignment information associated with the identified features may be utilized to straighten the depicted scene.

Abstract: According to example embodiments, a method for deinterlacing an image having a plurality of pixels, the method comprising: calculating a difference between a first pixel of the image and each pixel of at least one pixel pair, each pixel pair comprising one pixel being positioned above the first pixel and another pixel being positioned below the first pixel; and deinterlacing the first pixel only if at least one difference corresponding to a pixel pair exceeds a predefined threshold. A corresponding apparatus and computer program product are also provided.

Abstract: An apparatus, system, method, and article to continue border lines into an unknown region of an image from a known background; determine segments, based on the continued borders, for the unknown region of the image; and propagate pixels from a known area of the image to the unknown area based on the determined segments and continued borders.