Abstract: Described is a system which is capable of capturing images of the iris up to distances of 11 meters with a resolution of 150-200 pixels across the diameter. The system incorporates velocity estimation and focus tracking modules such that that images may be acquired from moving subjects.

Abstract: The image processing apparatus includes an area dividing part that divides an input image produced by an image pickup system into plural image areas whose evaluation values are mutually different. The evaluation value is obtained by using a response function of the image pickup system. The apparatus further includes a processing part that performs image processing to produce an output image whose definition is higher than that of the input image by using the response functions different for the respective image areas.

Abstract: Systems, methods, and media for on-line boosting of a classifier are provided, comprising: receiving a training sample; for each of a plurality of features, determining a feature value for the training sample and the feature, using the feature value to update a histogram, and determining a threshold for a classifier of the feature; for each of the plurality of features, classifying the training sample using the threshold for the classifier of the feature and calculating an error associated with the classifier; selecting a plurality of best classifiers from the classifiers; and, for each of the plurality of best classifiers, assigning a voting weight to the one of the plurality of best classifiers.

Abstract: The present invention concerns a method for correcting a digital image stored by a client device by geometric adjustment of this image onto a reference image stored by a server device connected to the client device by a communication network.

Abstract: An image processing apparatus capable of reducing processing load by determining whether or not to perform gradation correction, according to a difference or a ratio between feature values of object areas, and generating an excellent image by performing gradation correction. An image dividing section divides an input image into a plurality of predetermined object areas. A feature value calculation section and a determination section compare the feature values indicative of features of the respective object areas, obtain a luminance level difference, and determine whether or not the difference is within a predetermined range. When the difference is within the predetermined range, an image processing section and a system controller perform area-by-area tone mapping on respective images of the areas to form a synthesized image.

Abstract: An image processing apparatus and method of a camera is provided for compensating for shutter lag. An image processing apparatus includes an image scaler which scales a camera output image to a viewing image, a buffer which buffers the camera output image, a multiplexer which multiplexes outputs of the image scaler and the buffer, an image processor which processes multiplexed images corresponding to the multiplexed outputs of the image scaler and the buffer, a demultiplexer which demultiplexes an output of the image processor so as to supply the viewing image to a display unit, a codec which encodes the camera output image output by the demultiplexer into a capture image, and a controller which controls the multiplexer and the demultiplexer in a time divisional manner within a frame duration such that the image processor processes the viewing and camera output image sequentially in a capture mode.

Abstract: A radiographic imaging system is adapted to reconstruct a tomographic image in a given cross section of a subject from projection images of a subject acquired in tomosynthesis imaging. The radiographic imaging system comprises a frequency filtering processor for producing band limiting image signals having different frequency response characteristics from projection image signals corresponding to the projection images; a non-linear conversion processor for performing non-linear conversion of band limiting image signals to reduce a portion of band limiting image signals exceeding a given value; an integration processor for adding up band limiting image signals having undergone non-linear conversion through the non-linear conversion processor to produce converted image signals; and a back projection processor for reconstructing the tomographic image in the given cross section of the subject from the converted image signals corresponding to the projection images.

Abstract: Provided are a method and apparatus for processing an image to remove fog from the image. The apparatus for processing an image includes: a transmission estimation unit configured to calculate a transmission of an input image by synthesizing pixel-based transmissions of current pixels of the current image including a fog component, and block-based transmissions of a plurality of blocks of a previous image, each block including a plurality of pixels; an airlight estimation unit configured to calculate airlight of the input image; and an image restoration unit configured to generate, based on the transmission and the airlight, a restored image in which the fog component is removed from the current image.

Abstract: A method for deblurring a blurry image (18) includes utilizing a spatial mask and a variable splitting technique in the latent sharp image estimation cost function. Additionally or alternatively, the method can include the utilizing a spatial mask and a variable splitting technique in the PSF estimation cost function. The spatial mask can be in a regularization term of either or both the latent sharp image estimation cost function and the PSF cost function. The latent sharp image estimation cost function can be used for non-blind deconvolution. Alternatively, one or both cost functions can be used for blind deconvolution.

Abstract: Important information about an object is detected using less arithmetic processing. An object detection unit generates an edge image from a color image. The object detection unit evaluates symmetry of an image included in the edge image by performing processing in accordance with the position of a target pixel. The object detection unit identifies a symmetry center pixel forming an object having symmetry. The object detection unit detects an object width for each symmetry center pixel. The object detection unit identifies the width of the object in the vertical direction based on the width of the symmetry center pixels in the vertical direction, and identifies the width of the object in the horizontal direction based on the object width identified for each symmetry center pixel.

Abstract: A method for deblurring a blurry image (18) includes utilizing a spatial mask and a variable splitting technique in the latent sharp image estimation cost function. Additionally or alternatively, the method can include the utilizing a spatial mask and a variable splitting technique in the PSF estimation cost function. The spatial mask can be in a fidelity term in either or both the latent sharp image estimation cost function and the PSF cost function. The latent sharp image estimation cost function can be used for non-blind deconvolution. Alternatively, one or both cost functions can be used for blind deconvolution.

Abstract: According to an embodiment, an image processing device includes a generator and a processor. The generator is configured to generate, from a plurality of unit images in which points on an object are imaged by an imaging unit at different positions according to distances between the imaging unit and the positions of the points on the object, a refocused image focused at a predetermined distance. The processor is configured to perform blurring processing on each pixel of the refocused image according to an intensity corresponding to a focusing degree of the pixel of the refocused image.

Abstract: An electronic device includes a camera device for capturing images and a fingerprint identification unit for receiving signals of fingerprints. The electronic device detects a signal received from the fingerprint identification unit, and controls the camera device to focus a specified scene of the camera device and capturing an image of the specified scene, when the detected signal is a press signal.

Abstract: A diagnostic image generating apparatus, a medical image system, and a beamforming method are provided. The diagnostic image generating apparatus includes a transmitting unit configured to transmit a modulated transmission signal to a subject, a reception beamforming unit configured to form a reception beam by beamforming echo signals reflected from the subject, a point spread function (PSF) estimating unit configured to estimate a PSF for each region according to the formed reception beam, a filtering unit configured to filter the formed reception beam according to the estimated PSF, and a diagnostic image generating unit configured to generate a diagnostic image according to the filtered reception beam.

Abstract: An image processing method applicable to images captured by a wide-angle zoomable lens is provided. Said method comprising steps of: A. utilizing the wide-angle zoomable lens to photograph a calibration pattern under a predetermined focal length to obtain a distorted image corresponding to the calibration pattern; B. calculating a distortion parameter for the wide-angle zoomable lens at the predetermined focal length; C. utilizing the wide-angle zoomable lens to photograph an object under another focal length to obtain another distorted image corresponding thereto; D. calculating a new distortion parameter by using the distortion parameter obtained from Step B and a multiple relation between said another focal length and the predetermined focal length; and E. using the new distortion parameter to perform distortion correction on said anther distorted image corresponding to the object. The present invention can perform distortion correction for real-time images captured by the wide-angle zoomable lens.

Abstract: An image capturing device includes a pre-capturing module, a conversion module, a division module, a ranging module, a calculation module, and an image capturing module. The pre-capturing module obtains an initial image of a view the image capturing device to be captured. The conversion module converts the initial image to a gray scale image. The division module divides the gray scale image into multiple areas. The ranging module calculates an object distance collection of each area, and generates a total object distance collection by integrating the object distance collections. The calculation module calculates image capturing condition which makes a plurality of depth-of-field cover the total object distance collection. The image capturing module captures a plurality of images according to the image capturing condition to form an image array. An image capturing method is also provided.

Abstract: An image capturing apparatus includes an image capturing unit and an image processing unit. The image capturing unit captures a subject by an image sensor including focus detection pixels. The image processing unit includes a correction range determination unit configured to determine a range of a correction coefficient based on an optical condition of a photographing optical system, and a correction coefficient calculation unit configured to calculate the correction coefficient based on pixel data of a pixel positioned near the focus detection pixel, and a pixel correction unit configured to correct the pixel data of the focus detection pixel based on the correction coefficient and the range.

Abstract: A light diffraction element comprising a transparent substrate and a first orientation layer that is formed on one surface of the substrate and includes anisotropic polymers and a first pattern of an orientation direction arranged periodically in a first direction along the primary plane of the substrate. The first pattern includes three or more small regions that are arranged in the first direction and in which the orientation direction of the polymers included in the first orientation layer are different from each other, and generates diffracted light as a result of interference between light passed respectively through the three or more small regions.

Abstract: A microscope including an imaging optical unit, a sample stage for supporting a sample to be examined, a movement unit, by which the distance between sample stage and imaging optical unit can be altered, a focus measuring unit, which measures the present focus position and outputs a focus measurement signal, a control unit for maintaining a predetermined focus position for examinations of the sample that are separated from one another in time. The control unit receives the focus measurement signal and derives a deviation of the present focus position from the predetermined focus position. Dependent on the deviation derived the movement unit, changes the distance between sample stage and imaging optical unit so that the predetermined focus position is maintained. The control unit drives the movement unit (9) for maintaining the predetermined focus position only before and/or after at least one of the examinations, but never during the examinations.

Abstract: The described implementations relate to enhancing images. One system includes a lens configured to focus an image on an image sensor. The image sensor is configured to capture the image. The model of the lens can be known to the system. The system can also include an image enhancement component configured to receive the captured image and to utilize a simulated blur kernel of the known model to produce an enhanced image.

Abstract: Systems (490), methods (340), and machine-readable and executable instructions (428) are provided for depth mask assisted video stabilization. Depth mask assisted video stabilization can include creating a first depth mask from a first frame (101, 201) and a second depth mask from a second frame (102, 202) to obtain depth information (342) and defining a first list of feature points (111-1a, 111-2a, 111-3a, 111-4a, 113-1a, 113-2a, 113-3a, 113-4a, 113-5a) from the first frame (101, 201) and a second list of feature points (111-1b, 111-2b, 111-3b, 111-4b, 113-1b, 113-2b, 113-3b, 113-4b, 113-5b) from the second frame (102, 202) (344).

Abstract: A system for performing an enhanced scene detection procedure including a sensor device for capturing blur images of a photographic target. The blur images each correspond to a scene type that is detected from a first scene type which is typically a pillbox blur scene, and a second scene type which is typically a Gaussian scene type. A scene detector performs an initial scene detection procedure to identify a candidate scene type for the blur images. The scene detector then performs the enhanced scene detection procedure to identify a final scene type for the blur images.

Abstract: A focus adjusting device which includes an edge detection unit that detects edges of a subject image for each color component forming an image including the subject image; a distribution detection unit that detects distributions of a focalized state and an unfocused state of the image based on the edges detected by the edge detection unit; and a control unit that moves a lens based on the distributions detected by the distribution detection unit, wherein the subject image is incident from an optical system having the lens, the control unit moves the lens, and thus the subject image is focused on.

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: Provided is a method and apparatus for deblurring a non-uniform motion blur in an input image, that may restore a clearer image by dividing a large scale input image into tiles corresponding to partial areas, selecting, among the divided tiles, an optimal tile for a partial area most suitable for estimating non-uniform motion blur information, and effectively removing an artifact in an outer portion of a tile through padding of each tile.

Abstract: There is provided an image processing device including a weight calculation unit that calculates a weight corresponding to each of a plurality of pixel values centering on a pixel of interest of an input image based on a feature amount calculated based on the plurality of pixel values centering on the pixel of interest, a regression coefficient reading unit that reads a regression coefficient stored for each class code determined based on a plurality of pixel values corresponding to the pixel of interest of the input image, and a pixel value calculation unit that calculates a pixel value of a pixel of interest of an output image by performing calculation using the plurality of pixel values, the weights, and the regression coefficients centering on the pixel of interest of the input image.

Abstract: An image processing device includes an image acquirer for acquiring an image, a depth of field calculator for calculating an estimate representing a depth of field of an image based on collateral information of the image, an image divider for dividing the image into evaluation regions, and a blur evaluator for detecting a blur in each of the evaluation regions divided by the image divider, performing blur evaluation for calculating evaluation values for evaluating degrees of an out-of-focus blur or a camera/subject movement-caused blur, and calculating an evaluation value of the image from the evaluation values of the evaluation regions based on the estimated depth of field.

Abstract: An image classification program that is executed by a computer includes a first processing step of calculating feature values on the basis of the pixel densities of images, a second processing step of performing calculating in a space defined by the feature values, and a third processing step of grouping images that correspond to feature values that have been divided by the clustering.

Abstract: A method and system for image stabilization through image processing, and a zoom camera including an image stabilization function. The method includes: determining whether an input image comprises a representative feature portion; sampling the representative feature portion to generate a sampled image if it is determined that the input image comprises the representative feature portion; enlarging the input image by an optical zooming, matching the enlarged input image with the sampled image, and obtaining a central coordinate of the enlarged input image and a central coordinate of the sampled image; and aligning an optical axis by calculating a difference between the central coordinate of the enlarged input image and the central coordinate of the sampled image.

Abstract: Systems and methods can be configured to perform operations related to digital image processing. In a general aspect, this disclosure describes systems and methods relating to processing digital images for imaging system characterization and image quality enhancement. In some implementations, a method for digital image processing includes measuring a first phase transfer function (PTF) of a first digital image and a second PTF of a second digital image. The second digital image captures a spatially shifted version of the first digital image. The first PTF and the second PTF are compared and a spatial shift of the second image to the first image is determined.

Abstract: An auto focus image system that includes a pixel array coupled to a focus signal generator. The pixel array captures an image that has at least one edge. The focus signal generator may generate a focus signal that is a function of a width of the edge and/or statistics of widths of edges. A processor receives the focus signal and/or the statistics of the widths and adjusts a focus position of a focus lens. The width can be determined by various techniques including the use of gradients. An width determined along a prescribed direction is corrected for a slant of a boundary to which the edge belongs relative to the prescribed direction. The correction may use a peak gradient in the prescribed direction along the edge in conjunction with a largest gradient of a perpendicular direction within a predefined neighborhood of the peak gradient.

Abstract: A method for correcting overfocus of a digital image created from coherent imaging using centered fractional Fourier transforms or mathematical equivalents is described. A received image is presented to a numerical processor, and a first numerical value for an imaginary power variable is selected and used in an iterative algorithm, numerical procedure, system architecture, etc. A centered discrete fractional Fourier transform of an imaginary power and a phase restore operator associated are applied to the image file to produce a modified image. A change in mis-focused is determined and used in adjusting the specified imaginary power for a next iteration.

Abstract: The disclosure is directed to creating an inertial sensor aided depth map of a scene. An embodiment of the disclosure captures at least a first image and a second image during movement of a device caused by a user while framing or recording the scene, compensates for rotation between the first image and the second image, calculates an amount of translation of the device between the first image and the second image, calculates a pixel shift of a plurality of key points of the first image and the second image, and estimates a depth to one or more of the plurality of key points of the first image and the second image.

Abstract: Methods, media, and systems for assessing the quality of a digital image. In an embodiment, both a micro-analysis and macro-analysis are performed. The micro-analysis comprises dividing the digital image into a plurality of blocks, for two or more of the plurality of blocks, determining a score based on a spatial frequency of the block, and generating a score map for the digital image based on the score for each of the two or more blocks. The macro-analysis comprises detecting artifacts in the digital image, computing a degradation score based on detected artifacts, and computing a whole-slide-quality score based on the score map and the degradation score.

Abstract: This invention provides an image free from camera shake by using a plurality of images captured by a camera array image capturing apparatus. A determination unit determines whether to execute a camera shake correction processing. A memory unit temporarily stores only a group of images determined by a determination unit to be camera shake corrected. A camera shake correcting unit synthesizes images to correct blurs in the images. A matching point searching unit determines matching pixels by checking pixel value similarity between images. A moving amount calculating unit, based on the result acquired by the matching point searching unit, calculates a moving amount of each pixel between images. A position correcting unit, based on the moving amount of each pixel calculated by the moving amount calculating unit, corrects the positions of the images. An image synthesizing unit synthesizes a group of images that are position-corrected by the position correcting unit.

Abstract: An intensity image is collected at each of a plurality of locations spaced apart in a propagation direction of a light beam. Information from the intensity images is combined using a Kalman filter which assumes that at least one co-variance matrix has a diagonal form. This leads to considerable reduction in computational complexity. An augmented Kalman filter model (augmented space state model) is used in place of the standard Kalman filter model. The augmented Kalman filter improves the robustness to noise.

Abstract: According to one embodiment, an electronic apparatus includes a line recognition module, a character recognition module and a generator. The line recognition module recognizes lines in a handwritten document. The character recognition module recognizes character codes corresponding to handwritten characters in a first line and a second line which follows the first line. The generator generates, if the first and second lines satisfy a condition, document data using first character codes corresponding to the first line and second character codes corresponding to the second line, the formed document data including either one of the first character codes at a position of the second line or including at least one of the second character codes at a position of the first line.

Abstract: Provided is an image processing device that can bring about the sufficient resemblance between an original image and a restored image obtained corresponding to a low resolution input image. The image processing device includes a means that uses a dictionary for storing data associating deteriorated patches which are from a deteriorated image formed by deteriorating a prescribed image, and restoration patches which are from the prescribed image, and calculates, as a degree-of-similarity between plural input patches generated by dividing an input image and the deteriorated patches, a weighted degree-of-similarity between weighted deteriorated patches and weighted input patches, in which forms of the deteriorated patches and the input patches are reconfigured using a patch weight which is continuous weighting; a means that selects, on the basis of the weighted degree-of-similarity, a restoration patch for each input patch; and a means that combines the restoration patches to generate a restored image.

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: Reference free tracking of position by a mobile platform is performed using images of a planar surface. Tracking is performed optical flow techniques, such as pyramidal Lucas-Kanade optical flow with multiple levels of resolution, where displacement is determined with pixel accuracy at lower resolutions and at sub-pixel accuracy at full resolution, which improves computation time for real time performance. Periodic drift correction is performed by matching features between a current frame and a keyframe. The keyframe may be replaced with the drift corrected current image.

Abstract: The image processing apparatus includes a determining part configured to determine, from a difference between information on color of a first pixel in a first image and information on color of a second pixel corresponding to the first pixel in a second image, whether or not the first image includes color blur due to defocus, the first and second images being generated by an image-pickup system and whose focus states are mutually different. The apparatus further includes a correcting part configured to perform on the first image a correction process that corrects the color blur determined by the determining part.

Abstract: Image processing includes: receiving an image; applying shader code, using one or more processors, to the image to generate a blurred image version (BIV); receiving configuration information pertaining to a mask; generating the mask that includes an unblurred region and a blurred region, based at least in part on the configuration information; and applying the mask to combine the image and the BIV to render a composite image that includes an unblurred portion comprising a portion of the image corresponding to the unblurred region of the mask, and a blurred portion comprising a portion of the BIV corresponding to the blurred region of the mask.

Abstract: A method for deriving a blur kernel from a blurred image is provided herein. The method may include the following steps: obtaining a blurred image B, being a product of a blur kernel k applied to an original image I; calculating f?(x)=Rd*P?(B)(x) for every angle ?, wherein R denotes an autocorrelation operator, P? denotes a projection operator of based on angle ?, and d denotes a one dimensional differentiation filter; estimating spectral power of the blur kernel based on a given support parameter; estimating the blur kernel k using a phase retrieval algorithm, based on the estimated spectral power of the blur kernel; updating the support parameters; and repeating the estimating of the spectral power, the estimating of the kernel and the updating of the support parameters in an iterative, to yield the blur kernel.

Abstract: A computer-implemented method for viewing images on an interactive computing device comprises displaying an image from a stack comprising a display image and at least one compressed sub-image of nominally the same scene, each of the sub-images of the stack having been acquired at respective focal distances. Responsive to a user selecting a portion of the displayed image, the selected portion is mapped to a corresponding mapped portion of a sub-image within the stack according to the difference in focal distances between the displayed image and the sub-image. At least one row of compressed image blocks of the at least one sub-image extending across the mapped portion; and a reference value for a point in the compressed image stream of the sub-image preceding the row of compressed image blocks is determined.

Abstract: A method and apparatus for simulating depth of field (DOF) in microscopic imaging, the method comprising computing a blur quantity for each pixel of an all-focus image, performing point spread function operations on one or more regions of the all-focus image, computing intermediate and normalized integral images on the regions and determining an output pixel for the each pixel based on the intermediate and normalized integral images.

Abstract: A non-transitory computer-readable storage medium storing an image processing program causing a computer to execute an image processing on image data to be processed, the image processing program including an obtaining step obtaining the image data, a gradation conversion processing step performing gradation conversion processing on the image data at an intermediate part of gradation according to input/output characteristics having characteristics to which characteristics to reduce a contrast are added, and a correcting step making a correction to enhance a local contrast indicative of contrast at a local part of an image for the image data subjected to the gradation conversion processing by using a gain curve in which a degree of enhancement changes in accordance with luminance information of a pixel to be processed, and thus, bright and dark part gradations are improved while suppressing a change in a hue and color saturation as well as maintaining an apparent contrast.

Abstract: A method for improving depth for field (DOF) in microscopic imaging, the method comprising combining a sequence of images captured from different focal distances to form an all-focus image, comprising computing a focus measure at every pixel, finding the largest peaks at each position in the focus measure as multiple candidate values and blending the multiple candidates values according to the focus measure to determine the all-focus image.

Abstract: An image processing apparatus is arranged to process a first relatively underexposed and sharp image of a scene, and a second relatively well exposed and blurred image, nominally of the same scene, the first and second images being derived from respective image sources. The apparatus provides a portion of the relatively first underexposed image as an input signal to an adaptive filter; and a corresponding portion of the second relatively well exposed image as a desired signal to the adaptive filter. The adaptive filter produces an output signal from the input signal and the desired signal; and an image generator constructs a first filtered image from the output signal, relatively less blurred than the second image.

Abstract: A method of modifying the blur in at least a part of an image of a scene captures at least two images of the scene with different camera parameters to produce a different amount of blur in each image. A corresponding patch in each of the captured images is selected each having an initial amount of blur is used to calculate a set of frequency domain pixel values from a function of transforms of the patches. Each of the pixel values in the set are raised to a predetermined power, forming an amplified set of frequency domain pixel values. The amplified set of frequency domain pixel values is combined with the pixels of the patch in one of the captured images to produce an output image patch with blur modified relative to the initial amount of blur in the image patch.

Abstract: An apparatus for compensating for pixel distortion while reproducing hologram data includes an extraction unit, a determination and calculation unit, a table, and a compensation unit. The extraction unit extracts a reproduced data image from a reproduced image frame including the reproduced data image and borders. The determination and calculation unit determines position values of edges of the extracted reproduced data image, and calculates average magnification error values of pixels within line data from position values of start and end point pixels thereof, which are based on the determined position values of the edges. The table stores misalignment compensation values for the pixels within the line data, wherein the misalignment compensation values correspond to predetermined references for average magnification error values.