Abstract: The subject disclosure is directed towards communicating image-related data between a base station and/or one or more satellite computing devices, e.g., tablet computers and/or smartphones. A satellite device captures image data and communicates image-related data (such as the images or depth data processed therefrom) to another device, such as a base station. The receiving device uses the image-related data to enhance depth data (e.g., a depth map) based upon the image data captured from the satellite device, which may be physically closer to something in the scene than the base station, for example. To more accurately capture depth data in various conditions, an active illumination pattern may be projected from the base station or another external projector, whereby satellite units may use the other source's active illumination and thereby need not consume internal power to benefit from active illumination.

Abstract: A method for normalizing at least one character included in an image is provided. The method includes steps of: (a) an apparatus for normalizing a specific character adding or supporting to add at least one margin, which is determined by referring to information on at least one another character related to the specific character detected in the image, around a bounding box which includes the specific character; and (b) the apparatus normalizing or supporting to normalize an area of the bounding box around which the at least one margin is added.

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: An image encoding method for an encoding system includes receiving a first image captured by a main camera and a second image captured by a sub camera provided in the same plane; comparing pixel values of pixels at first coordinates of each of the first and second images to obtain a first difference value; determining the first coordinates are in surface or back region in case of the first difference value is not more than or more than a first threshold value; pixel-shifting the second image by a first shift amount; and comparing the pixel value at the first coordinates of the first image with that of the second image after the pixel shift to obtain a second difference value, determining whether the first coordinates are in the surface or back region based on the second difference value, and recording into a second frame different from the first frame.

Abstract: An image composition apparatus according to the present invention comprising: an image acquiring section for acquiring first image data and second image data; a subtraction processing section for obtaining a difference value for each pixel for at least a part of the first image data and at least a part of the second image data; a filter processing section for applying filter processing based on a spatial frequency of an image to the difference value; and an image composition section for compositing at least a part of the first image data with at least a part of the second image data on the basis of an output of the filter processing.

Abstract: A lossy compression method optimizes bandwidth and storage for a security surveillance network. An appliance on a local network attached to event capture terminals transforms image files into a key frame and at least one subsequent frame. Decompression combines a subsequent frame with its key frame to provide an image with graduated resolution/noise clutter. A camera records, and forwards a plurality of image files compatible with JPEG. Key frames are selected from among the plurality of image files. A configurable low pass filter is reset for each train of a key frame and its subsequent frames. Each low pass filter is selectively applied to each pixel block within a subsequent frame. The transformation operates on coefficients of frequency bins. Meta data enables decompression of a single subsequent frame by reversing some of the transformations to provide a JPEG compatible file having selectively reduced resolution or noise clutter.

Abstract: Methods and systems for dehazing images with increased accuracy and reduced error enhancement. In particular, one or more embodiments estimate a transmission map representing an amount of unscattered light reflected from objects in an input image. One or more embodiments refine the transmission map to obtain transmission information consistent with a depth of the objects in the input image. One or more embodiments also determine a radiance gradient for the input image. One or more embodiments generate an output image from the input image by removing haze based on the refined transmission map and preventing error enhancement based on the determined radiance gradient.

Abstract: A processing device receives input representing a selection of one or more areas of an image and creates a blurred area for the one or more selected areas. The blurred area corresponds to a portion of the image that contains the one or more selected areas. The portion of the image has a size that is greater than an aggregate size of the one or more selected areas. The processing device replaces the one or more selected areas with the corresponding portion of the blurred area.

Abstract: A bilateral filtering method includes decomposing an image patch by pixel intensity to form a stack of patches; computing spatial filtering response of each intensity; multiplying the spatial filtering response of each intensity by corresponding intensity, thereby resulting in multiplied spatial filtering response of each intensity; and summing up the multiplied spatial filtering responses of different intensities weighted with corresponding range weights.

Abstract: An image processing apparatus includes a gain calculation unit that calculates a gain for each of a plurality of pixels of an image signal, respectively, and an addition unit that adds the gain for each pixel to the corresponding pixel of the plurality of pixels of the image signal. The gain calculation unit includes a first order differential operation unit that calculates a first value from first order differential of the image signal for each of the plurality of pixels and second order differential operation unit that calculates a second value from a second order differential of the image signal for each of the plurality of pixels, and calculates the gains for each pixel based on the first and second values for each pixel.

Abstract: Methods, systems, computer-readable media, and apparatuses for fast cost aggregation for dense stereo matching are presented. One example method includes the steps of receiving first and second images of a scene; rectifying the images; computing a cost volume based on the first and second images; subsampling the cost volume to generate a subsampled cost volume; for each pixel, p, in the subsampled cost volume, determining one or more local extrema in the subsampled cost volume for each neighboring pixel, q, within a window centered on the pixel, p; for each pixel, p, performing cost aggregation using the one or more local extrema; performing cross checking to identify matching pixels; and responsive to identifying unmatched pixels, performing gap-filling for the unmatched pixels to generate a disparity map; and generate and storing a depth map from the disparity map.

Abstract: An image processing apparatus includes a detection unit that detects segments from a first image; a selection unit that selects pairs of segments formed of a predetermined number of segments counted from a higher priority in an order of length among the detected segments and segments in a second image, the second image being a model of the first image; and a calculation unit that calculates distortion of the first image with respect to the second image by using the pairs of segments.

Abstract: A computer program product includes instructions for a processor to perform a method of improving image structure and coherence, and/or for simplification/stylization. The method includes inputting the image, by: scanning the image; image capture using a camera; and/or image creation using a computer. Multi-channel images are converted into a single-channel image, which is separated into a first image component—the high spatial frequencies, and a second component image—the low spatial frequencies. The first and second component images are each formed by filtering to remove frequencies outside of respective upper and lower threshold frequencies. A gain multiplier is applied to the filtered first and second component images to control detail amplification. The first and second component images are each blurred at the respective upper and lower threshold frequencies.

Abstract: A depth-sensing camera may be used to locate objects on a planar surface. A planar fit calculation is used to model the surface. One problem with the best planar fit calculation is that it is not robust over time. Firstly, this is because the depth data has a non-linear curve near its extremities because of camera lens distortion. Secondly, as the depth-sensing camera warms up and its thermal activity changes, the depth data drifts and the initial plane fit is no longer valid. The position and the amount of curvature and drift may be different for cameras of the same make and model in some cases. In accordance with some embodiments, algorithms may be used to detect and correct for these types of errors to support more robust plane fitting in real time.

Abstract: A method, apparatus and computer program product are provided to cause image content to be adjusted in a manner consistent with the corresponding viewing direction, such as the viewing direction of a user of a head-mounted display device. In regards to a method, one or more first anchor frames are determined within a multi-frame image, a user's viewing direction is determined relative to the multi-frame image and at least one second anchor frame is identified based on the user's viewing direction. The method also includes determining one or more tonal modification parameters of a frame in relation to the viewing direction based upon the one or more first anchor frames and the at least one second anchor frame. Further, the method generates a plurality of modified frames based on the one or more tonal modification parameters. A corresponding apparatus and computer program product are also provided.

Abstract: A super-resolution method for generating a high-resolution (HR) image from a low-resolution (LR) blurred image is provided. The method is based on a transform-invariant directional total variation (TI-DTV) approach with Schattenp=1/2 (S1/2-norm) and L1/2-norm penalties. The S1/2-norm and the L1/2-norm are used to induce a lower-rank component and a sparse component of the LR blurred image so as to determine an affine transform to be adopted in the TI-DTV approach. In particular, the affine transform is determined such that a weighted sum of the S1/2-norm and the L1/2-norm is substantially minimized. Based on the alternating direction method of multipliers (ADMM), an iterative algorithm is developed to determine the affine transform. The determined affine transform is used to transform a candidate HR image to a transformed image used in computing a directional total variation (DTV), which is involved in determining the HR image.

Abstract: A character recognition apparatus includes a storage and a processor that executes a method including generating input stroke data from input coordinate data corresponding to an input operation, generating stroke combination candidates and evaluation data corresponding to the stroke combination candidates from the input stroke data, the stroke candidates including target verification strokes combined to constitute target verification characters, identifying a first stroke combination from the stroke combination candidates based on appearance probability of the target verification strokes, appearance probability data of each stroke stored in the storage, and the evaluation data, and outputting a character corresponding to the input operation based on the first stroke combination. The appearance probability indicates a probability in which the target verification strokes appear in each of the target verification characters.

Abstract: Various systems and methods for providing a repositionable video display on a mobile device, to emulate the effect of user-controlled binoculars, are described herein. In one example, one or more high resolution video sources (such as UltraHD video cameras) obtain video that is wirelessly broadcasted to mobile devices. The mobile device processes the broadcast based on the approximate location of the spectator's mobile device, relative to a scene within the field of view of the mobile device. The location of the mobile device may be derived from a combination of network monitoring, camera inputs, object recognition, and the like. Accordingly, the spectator can obtain a virtual magnification of a scene from an external video source displayed on the spectator's mobile device.

Abstract: Systems, devices, and methods for material recognition extract one or more features from a patch in an image of a scene; generate an initial prediction of a material category of the patch from candidate material categories based on the one or more features; identify a scene in the image; identify one or more objects in the image; obtain a first relationship model of two or more of the one or more features, the candidate material categories, the one or more objects, and the scene; and make a refined prediction of the material category of the patch based on the initial prediction of the material category and on the first relationship model.

Abstract: A method of determining an output frame rate includes receiving an input sequence of frames of image data at an input frame rate, performing motion vector calculations on the frames of image data to produce motion vectors and motion statistics, determining a motion level in the frames using the motion statistics, and interpolating frames of image data at the output frame rate, wherein the output frame rate is based upon the motion level.