Abstract: Provided are mechanisms and processes for augmenting multi-view image data with synthetic objects using inertial measurement unit (IMU) and image data. In one example, a process includes receiving a selection of an anchor location in a reference image for a synthetic object to be placed within a multi-view image. Movements between the reference image and a target image are computed using visual tracking information associated with the multi-view image, device orientation corresponding to the multi-view image, and an estimate of the camera's intrinsic parameters. A first synthetic image is then generated by placing the synthetic object at the anchor location using visual tracking information in the multi-view image, orienting the synthetic object using the inverse of the movements computed between the reference image and the target image, and projecting the synthetic object along a ray into a target view associated with the target image.

Abstract: An imaging device including a pixel matrix and a processor is provided. The pixel matrix includes a plurality of phase detection pixels and a plurality of regular pixels. The processor performs autofocusing according to pixel data of the phase detection pixels, and determines an operating resolution of the regular pixels according to autofocused pixel data of the phase detection pixels, wherein the phase detection pixels are always-on pixels and the regular pixels are selectively turned on after the autofocusing is accomplished.

Abstract: A control unit includes a controller controlling a polarization state of a liquid crystal layer of a liquid-crystal low pass filter to be any of a first polarization state, a second polarization state, and an intermediate polarization state between the first polarization state and the second polarization state. In output of a plurality of image data from an imaging element, the controller controls the polarization state of the liquid crystal layer to be the first polarization state or the second polarization state when first image data of the image data is outputted, and the controller controls the polarization state of the liquid crystal layer to be the intermediate polarization state when one or more of second and subsequent ones of the image data are outputted.

Abstract: A device and method for three-dimensional reconstruction of a scene by image analysis is provided. This device comprises an image acquisition device to capture images of the scene, an analysis device to calculate a three-dimensional reconstruction of the scene from at least one image of the scene taken by the image acquisition device, and a projection device to project a first light pattern and a second light pattern, which are complementary, on the examined scene, the first light pattern and the second light pattern being projected along separate projection axes forming a non-zero angle between them, so as to be superimposed while forming a uniform image with homogenous intensity in a projection plane.

Abstract: According to one embodiment, a system includes a processor and logic in and/or executable by the processor to cause the processor to: initiate a capture operation using an image capture component of the mobile device, the capture operation comprising; capturing video data; and estimating a plurality of motion vectors corresponding to motion of the image capture component during the capture operation; detect a document depicted in the video data; track a position of the detected document throughout the video data; select a plurality of images using the image capture component of the mobile device, wherein the selection is based at least in part on: the tracked position of the detected document; and the estimated motion vectors; and generate a composite image based on at least some of the selected plurality of images.

Abstract: A method of modification of audio data to improve the quality of the audio modification or reconstruction or improves the speed of such reconstruction or modification and produces more realistic audio data. Realistic audio data is audio data that is generated in natural events like talking or singing or a vehicle passing by and is not generated only by artificially constructing audio data like in a synthesizer. This will lead to audio data that will be perceived more likely as natural or unmodified audio signal when being played back to human beings. The method involves modification of some part of transformed audio data, especially phase data.

Abstract: A method for identifying an object in a search image, in which the object and surroundings around the object are recorded by an optics unit of a camera. The optics unit is swivelled in the surroundings during the integration of a recorded image and an image processing unit back calculates the search image from the recorded image using the point spread function and the swivelling movement of the optics unit. Then the search image is searched and the object is identified in the search image.

Abstract: Methods, computer program products, and computer systems for recovering data of scene are provided. The techniques include: obtaining, by at least one processor, data of a scene; re-sampling, by the at least one processor, the data of the scene to obtain re-sampled sensing data of the scene and a corresponding sensing matrix; and constructing, by the at least one processor, recovered data of the scene using the re-sampled sensing data of the scene and the corresponding sensing matrix. In one embodiment, the method includes enhancing occluded data of the scene to construct the recovered data of the scene, where the recovered data of the scene facilitates identification of the scene. In another embodiment, the method includes compressing original data of a scene, the compressing including sampling the original data of the scene to select the data of the scene.

Abstract: A video deblurring method based on a layered blur model includes estimating a latent image, an object motion and a mask for each layer in each frame using images consisting of a combination of layers during an exposure time of a camera when receiving a blurred video frame, applying the estimated latent image, object motion and mask for each layer in each frame to the layered blur model to generate a blurry frame, comparing the generated blurry frame and the received blurred video frame, and outputting a final latent image based on the estimated object motion and mask for each layer in each frame, when the generated blurry frame and the received blurred video frame match. Accordingly, by modeling a blurred image as an overlap of images consisting of a combination of foreground and background during exposure, more accurate deblurring results at object boundaries can be obtained.

Abstract: An image processing apparatus acquires a first image generated by image capturing, stores data about an image restoration filter that is used for an image restoration process and corresponds to a first F-number, stores interpolation data corresponding to each of a plurality of second F-numbers different from the first F-number, which relates to an interpolation proportion in an interpolation process, and generates, when an image capturing F-number as the F-number for the image capturing is one of the second F-numbers, a second image by performing for the first image a correction process that includes the image restoration process and the interpolation process, by using the image restoration filter corresponding to the first F-number and the interpolation data corresponding to the image capturing F-number.

Abstract: A method for deblurring a blurry image (400) includes the steps of: performing a first phase of deconvolution (202) with a first phase regularization spatial mask (300) to reconstruct the main edges and generate a first phase latent sharp image (404) having reconstructed main edges; and performing a second phase of deconvolution (204) with a second phase regularization spatial mask (304) to reconstruct the texture and generate a second phase latent sharp image (406). The second phase regularization spatial mask (304) can be different from the first phase regularization spatial mask (300).

Abstract: A method for generating HDR (High Dynamic Range) images, performed by a processing unit, is introduced to at least contain: acquiring a frame 0 and a frame 1; calculating a first MV (Motion Vector) between the frame 0 and the frame 1; acquiring a frame 2; predicting a second MV between the frame 0 and the frame 2 according to the first MV, a time interval between shooting moments for the frames 0 and 1 and a time interval between shooting moments for the frames 0 and 2; generating a first MD (Motion Detection) matrix comprising a plurality of first MD flags according to the second MV; and fusing the frame 0 with the frame 2 according to the first MD flags.

Abstract: An optical calibration system including a calibration module, a light source, an optical sensing device and a calculation module is provided. The calibration module includes a calibration plane and a plurality of calibration structures between the calibration plane and the light source, wherein the calibration structures are disposed at predetermined calibration positions. The light source projects a linear light section toward the calibration module. The optical sensing device senses reflected light from the calibration plane and the calibration structures reflecting the linear light section to generate a sensed frame. The calculation module calculates positions of gravity centers of a plurality of calibration points in the sensed frame corresponding to the calibration structures.

Abstract: Extracting card information comprises a server at an optical character recognition (“OCR”) system that interprets data from a card. The OCR system performs an optical character recognition algorithm an image of a card and performs a data recognition algorithm on a machine-readable code on the image of the card. The OCR system compares a series of extracted alphanumeric characters obtained via the optical character recognition process to data extracted from the machine-readable code via the data recognition process and matches the alphanumeric series of characters to a particular series of characters extracted from the machine-readable code. The OCR system determines if the alphanumeric series and the matching series of characters extracted from the machine-readable code comprise any discrepancies and corrects the alphanumeric series of characters based on the particular series of characters extracted from the machine-readable code upon a determination that a discrepancy exists.

Abstract: To provide a mobile phone which can be used without hampering convenience in a condition where functions of the mobile phone are switched and can improve operability. The mobile phone includes an optical sensor, a display element, a pixel circuit portion where a plurality of pixels having a plurality of transistors are arranged in matrix, an optical sensor control circuit which is connected to an optical sensor driver circuit for driving the optical sensor and reads a signal from the optical sensor, a display portion control circuit which is connected to a display element driver circuit for driving the display element and outputs an image signal for displaying an image on a display portion, a gradient detection portion for outputting a signal in accordance with a gradient of the mobile phone, and an arithmetic circuit for performing display in the pixel circuit portion by switching image signals output to the display portion control circuit with a signal from the gradient detection portion.

Abstract: A digital magazine server determines a dominant color present in an image using a clustering algorithm. Color components of each pixel in the image are identified used to generate vectors associated with each pixel. Based on the vectors associated with the pixels, clusters including one or more pixels are generated using a clustering algorithm (e.g., k-means). The digital magazine server generates a characteristic vector for each cluster based on the vectors included in the cluster and selects a set of clusters based on their characteristic vectors. A centroid identifying the dominant color of the image is determined from the characteristic vectors of clusters in the set.

Abstract: A system for microscopic applications, including a rotating structural element that acts as a beam splitter and has reflecting and transmitting structures, and which is disposed in an intermediate image plane of the beam path conjugated with the object field, and by which the structure is imaged onto an object in the object plane. The fluorescent light reflected by the object, or caused by the illumination, strikes the structural element as well as an image processing module. The beam reflected and transmitted by the structural element is guided through the image processing module. The structural element is set at an angle to the vertical of the beam path. An optical adapter, which tilts the microscopic intermediate image onto the plane of the structural element acting as beam splitter, is disposed at the interface between the microscope and the image processing module.

Abstract: A non-transitory computer-readable storage medium storing an image processing program that causes a computer to execute an image processing method comprising acquiring step of acquiring an input image generated by image pickup through an optical system, generating step of generating a point spread function by using coefficient data of a function approximating a point spread function corresponding to an image-pickup condition of the optical system, and providing step of providing unsharp mask processing to the input image using a filter generated based on information of the point spread function generated by using the coefficient data. The filter is a filter having two-dimensional data.

Abstract: Systems and methods for detecting image anomalies include extracting one or more detected images from a submission file received from at least one computing device and generating an image identification (ID) for each of the one or more images. One or more image quality indices are determined for the submission file based on at least one of predetermined image features, an image type of the one or more images, and submission file attributes, and one or more image anomalies associated with the one or more images of the submission file are detected based on at least one of the image ID and the one or more image quality indices.

Abstract: The present invention provides a method and a device for detecting interest points in an image. The method includes: acquiring an original input image; performing down-sampling processing on the original input image, so as to obtain a plurality of sampling images with different resolutions; dividing each sampling image into a plurality of small image blocks; performing filtering processing on the plurality of small image blocks in each sampling image in sequence by using Laplacian-of-Gaussian filters, so as to obtain filtered images of the plurality of small image blocks in each sampling image; and acquiring interest points in an image in filtered images of the plurality of small image blocks in each sampling image. The present invention is used for solving the problems of more memory consumption and a low detection speed in the prior art.

Abstract: Deblurring a blurry image (14) includes the steps of (i) computing a spatial mask (256); (ii) computing a modified blurry image (264) using the blurry image (14) and the spatial mask (256); and (iii) computing a latent sharp image (16) using the modified blurry image (264) and a point spread function (260). Additionally, the image (714) to can be analyzed to identify areas of the image (714) that are suitable for point spread function estimation. Moreover, a region point spread function (1630) can be analyzed to classify the point spread function(s) as representing (i) motion blur, (ii) defocus blur, or (iii) mixed motion blur and defocus blur. A point spread function (2670) can also be estimated.

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: An image processing apparatus authenticates whether the same person as a person as a destination of transmission is photographed in light field data as an object, and when the person is photographed as the object, sets a focal distance of an object image of the person as the destination of transmission as a focal distance to be used for refocusing the light field data.

Abstract: Techniques related to image refocusing for camera arrays using a space variant filter based on a pixel by pixel blur level associated with a difference between a reference image and a basic refocused image are discussed. Such techniques may include taking the difference between the reference image and the basic refocused image and applying a space variant filter to the basic refocused image to generate a final refocused image having a region of increased blur with respect to the all in focus reference image. The blur level implemented by the space variant filter may be based on the difference and, optionally, the reference image noise level and the reference image gradient.

Abstract: Devices, systems, and methods of blind deblurring and blind super-resolution utilizing internal patch recurrence. Small signal patches tend to repeat “as is” across multiple scales of a natural signal. This fractal-like behavior is utilized for signal processing tasks, including “Blind Deblurring” or “Blind Super-Resolution”, namely, removing signal blur or increasing signal resolution without a-priori knowledge of the underlying blur kernel. While the cross-scale patch recurrence is strong in signals taken under ideal conditions, the cross-scale patch recurrence significantly diminishes when the acquisition blur deviates from an ideal blur. These deviations from ideal patch recurrences are used for recovering the underlying (unknown) blur kernel. The correct blur kernel is recovered by seeking the kernel which maximizes the patch similarity across scales of a related “reference” signal.

Abstract: An imaging apparatus includes an imaging unit for picking up an optical image of an object and generating image pickup data which can be refocused, a detection unit for detecting a focus state of the optical image of the object, a prediction unit for predicting an in-focus position of the optical image of the object on the basis of a detection result of the detection unit, and a focus adjustment unit for driving a focus lens on the basis of the in-focus position predicted by the prediction unit, wherein in a case where the imaging unit picks up a plurality of images from the object, the focus adjustment unit drives the focus lens to a position deviated from the in-focus position predicted by the prediction unit by a predetermined amount, and has a plurality of patterns of a position deviated by the predetermined amount.

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 method and optical system for determining a depth map of an image, the method including: determining a first focus measure of a first color in at least one region of the image; determining a second focus measure of a second color in the at least one region of the image; determining a ratio of the first and the second focus measure; and determining the depth map based on a ratio of the first and second focus measure.

Abstract: An image such as a light-field image may be captured with a light-field image capture device with a microlens array. The image may be received in a data store along with a depth map that indicates depths at which objects in different portions of the image are disposed. A function may be applied to the depth map to generate a mask that defines a gradual transition between the different depths. An effect may be applied to the image through the use of the mask such that applicability of the effect is determined by the mask. A processed image may be generated. The first effect may be present in the processed image, as applied previously. The processed image may be displayed on a display device. If desired, multiple effects may be applied through the generation of multiple masks, depth maps, and/or intermediate images prior to generation of the processed image.

Abstract: A fog in an image is quickly removed with a small processing load. An image processing device includes a dark channel image generating section 20 for generating a dark channel image based on an input image, a transmittance image generating section 30 for generating a transmittance image based on the dark channel image generated in the dark channel image generating section 20 and a pixel value of atmospheric light, a transmittance correcting section 40 for correcting the transmittance image generated in the transmittance image generating section 30, and a fog removal image generating section 60 for removing fog in the input image based on the transmittance image corrected in the transmittance correcting section 40, the pixel value of atmospheric light, and the input image.

Abstract: For calculating a sharpness value, a method filters an image with an edge extraction filter to generate filtered pixel values for each pixel of the image. The method further calculates a sharpness threshold as a function of the filtered pixel values. In addition, the method calculates a sharpness weight for each filtered pixel value as a function of the filtered pixel value and the sharpness threshold. The method calculates a weighted pixel value for each filtered pixel value as a function of the filtered pixel value and the corresponding sharpness weight for the filtered pixel value. The method further calculates a sharpness value for the image as a function of the weighted pixel values.

Abstract: A system, apparatus, method, and computer readable media for calibration of one or more extrinsic image sensor parameters. A system may calibrate a multi-camera surround view system, for example as may be employed in a vehicle, based on image data comprising one or more ground plane landmarks. The system may determine a ground plane projection of the image data, for example through a Radon transformation. A signal associated with at least one of the one or more ground plane landmarks in the ground plane projection(s) may be determined, for example through application of the projection-slice theorem. The landmark signal may be utilized as a response in an automated calibration loop to optimize one or more extrinsic parameter values associated with the sensors.

Abstract: An image processing apparatus detects a focus state of obtained LF data, and changes methods for recording the LF data, depending on the focus state. At this time, the image processing apparatus records a reconstructed image generated from the LF data without recording the LF data when the focus state of the LF data is an in-focus state, and records the LF data when the focus state of the LF data is in an out-of-focus state.

Abstract: A digital magazine server determines a dominant color present in an image using a clustering algorithm. Color components of each pixel in the image are identified used to generate vectors associated with each pixel. Based on the vectors associated with the pixels, clusters including one or more pixels are generated using a clustering algorithm (e.g., k-means). The digital magazine server generates a characteristic vector for each cluster based on the vectors included in the cluster and selects a set of clusters based on their characteristic vectors. A centroid identifying the dominant color of the image is determined from the characteristic vectors of clusters in the set.

Abstract: An imaging section of a microscope apparatus captures a plurality of microscope images each having the focal position which differs in the field being same with a light flux having passed through a microscopic optical system. A region separating section separates a cellular region from a non-cellular region by using the plurality of the microscope images. A focusing position calculating section finds a focusing position in a target pixel included in the cellular region based on a brightness change in the position being same in the plurality of the microscope images. A three dimensional information generating section generates three dimensional information of a cultured cell based on a position of the cellular region and the focusing position in the target pixel.

Abstract: An image processing apparatus and a method are provided. The image processing apparatus includes an accumulator for accumulating image data in which images are accumulated when the images are input from an image sensor, a memory for storing the pieces of image data that are output from the accumulator, and a processor for generating a final image using at least one image data from among the pieces of image data that are stored in the memory.

Abstract: A system for automatic focusing with a lens and methods for making and use the same are provided. When performing a focusing operation, a controller calculates a focus measure value for each lens position of a plurality of lens positions. The focus measure values are calculated based on each of the window evaluation values and a respective weight for image focusing windows within a set of image focusing windows. The controller then compares the calculated focus measure values of the plurality of lens positions in order to select an optimal lens position. The set of image focusing windows can be selected based on one or more sets of image focusing window selection rules derived from statistical data. In addition, the respective weights for image focusing windows can also be calculated based on the statistical data.

Abstract: A system, method, and computer program product for capturing images for later refocusing. Embodiments estimate a distance map for a scene, determine a number of principal depths, capture a set of images, with each image focused at one of the principal depths, and process captured images to produce an output image. The scene is divided into regions, and the depth map represents region depths corresponding to a particular focus step. Entries having a specific focus step value are placed into a histogram, and depths having the most entries are selected as the principal depths. Embodiments may also identify scene areas having important objects and include different important object depths in the principal depths. Captured images may be selected according to user input, aligned, and then combined using blending functions that favor only scene regions that are focused in particular captured images.

Abstract: A haze image discriminating apparatus has a first calculator to calculate a difference between a color difference component of an image signal of each of a plurality of pixels in an image and a gray value, and calculate a first ratio of pixels in which the difference is lower than a first reference value, to the plurality of pixels, a second calculator to calculate a second ratio of pixels in which a luminance component of the pixel signal of each of the plurality of pixels is lower than a second reference value, to the plurality of pixels, and a haze-degree determining unit to determine that a degree of haze of the image is higher as the first ratio is higher and the second ratio is lower.

Abstract: The perspective in the captured image is enhanced. Provided is an image processing apparatus including: a detecting section that detects a subject distance in each region of a captured image; and an image processing section that changes a distance perspective of an image of the region depending on the subject distance detected for each region of the captured image. In an example, the image processing section may increase the blue component ratio of a region whose detected subject distance is larger than a reference value. In an example, the image processing section may blur an image of a region whose detected subject distance is larger than a reference value.

Abstract: Methods, devices, and computer program products for multi-frame termporal de-noising using image alignment are describe. In one aspect, a method of capturing an image using a multi-frame temporal de-noising is described. The method includes capturing a plurality of frames and aligning the captured plurality of frames with each other. The method further includes determining a subset of frames of the captured plurality of frames, the subset determined based upon a focus quality of each frame of the plurality of frames. Finally, the method includes combining the subset of frames into a single image using a motion filter to reduce blurriness and ghosting.

Abstract: A system (300) for detecting whether an image (16) is blurred performs the steps of: identifying valid light trails in the test image (308), and classifying the test image as blurred if there is a sufficient number of matching valid light trails oriented in a repetitive pattern (310). The system (300) is designed to automatically detect whether a night scene image (16) is blurred based on the existence and characteristics of any light trails (552) in the captured image (16). Because the method extracts the characteristics of the light trails (552) and analyzes these light trails (552), it accurately detects blur in the challenging night scene images and has a relatively low false positive rate.

Abstract: Systems and methods of validating transcriptions of natural language content using crowdsourced validation jobs are provided herein. In various implementations, a transcription pair comprising natural language content and text corresponding to a transcription of the natural language content may be gathered. A first group of validation devices may be selected for reviewing the transcription pair. A first crowdsourced validation job may be created for the first group of validation devices. The first crowdsourced validation job may be provided to the first group of validation devices. A vote representing whether or not the text accurately represents the natural language content may be received from each of the first group of validation devices. A validation score may be assigned to the transcription pair based, at least in part, on the votes from each of the first group of validation devices.

Abstract: According to the present invention, even if variation (estimation variation) is caused in a subject distance estimated at the time of imaging when restoration processing of a taken image is performed using a restoration filter corresponding to the subject distance, since an optimal restoration filter that conforms to a subject distance taking into account the maximum infinity-side estimation variation and does not cause overcorrection is selected, it is possible to prevent resolution degradation due to overcorrection and achieve the improvement of resolution by the restoration filter.

Abstract: In an image pickup apparatus using an image pickup element including a plurality of photoelectric conversion means sharing a microlens, the number of pixels to be read is switched between the case of normal photographing and the case of live view driving. In the case of live view driving, only pixels positioned near the center of the optical axis of the microlens, the number of which is smaller than that in the case of normal photographing, are read. The image pickup apparatus realizes both normal photographing capable of acquiring an image in which the depth of field is small and which can be refocused, and live view photographing capable of displaying an image with a large depth of field and the high frame rate, thereby allowing the framing of the photographed image to be confirmed.

Abstract: A confocal image generation apparatus includes a laser, an objective, an optical path branch element which branches an optical path of an excitation light and an optical path of fluorescence, a scanning optics which shifts alight collecting position of the excitation light on a focal plane of the objective in an orthogonal direction to an optical axis of the objective, an optical detector in which a plurality of light-receiving elements are two-dimensionally arrayed with a shorter pitch than a diameter of a fluorescence Airy disk formed on an imaging plane that is optically conjugated with the focal plane, and an image operation unit which generates a confocal image of the sample in which a super-resolution component is emphasized on the basis of a signal that is output from the plurality of light-receiving elements, the super-resolution component being a frequency component that exceeds a cut-off frequency of the objective.

Abstract: An autofocus metric approach for focusing video images, automatically, based on images taken during a focus sweep in which a focus cell is repositioned for each of the images is provided. The approach includes, given an edge detected image from the focus sweep and an associated focus cell position in the focus sweep, an autofocus engine dividing the edge detected image into sub-images. For each sub-image, the autofocus engine calculates a normalized edge detection strength and compares it to a threshold. Based on the comparison, the autofocus engine determines whether an edge is present in the sub-image. Based on the determinations of edges in the sub-images, the autofocus engine calculates an autofocus metric associated with the given focus cell position. The autofocus engine provides the autofocus metric together with autofocus metrics associated with other focus cell positions to focus the video images.

Abstract: Systems, methods and program storage devices are disclosed, which comprise instructions to cause one or more processing units to analyze input images to a texture atlas and determine how each texture should be modified before being stored in the texture atlas to prevent undesirable drawing artifacts. For example, “tileable” images may be identified on a per-edge basis (e.g., by determining whether each edge pixel is above a certain opacity threshold). The tileable images may then be modified, e.g., by extruding a 1-pixel border identical to the outer row of pixels, before being stored in the texture atlas. “Character”-type sprites may also be identified on a per-edge basis (e.g., by determining whether each edge pixel is below the opacity threshold). The character-type sprites may then by modified by adding a single pixel transparent border around the outer rows of pixels before being stored in the texture atlas.

Abstract: Systems and methods are provided for providing improved de-noising image content by using directional noise filters to accurately estimate a blur kernel from a noisy blurry image. In one embodiment, an image manipulation application applies multiple directional noise filters to an input image to generate multiple filtered images. Each of the directional noise filters has a different orientation with respect to the input image. The image manipulation application determines multiple two-dimensional blur kernels from the respective filtered images. The image manipulation application generates a two- two-dimensional blur kernel for the input image from the two-dimensional blur kernels for the filtered images. The image manipulation application generates a de-blurred version of the input image by executing a de-blurring algorithm based on the two-dimensional blur kernel for the input image.

Abstract: A method for processing a blurred image (16) that includes a captured light trail (24) includes the steps of: (i) displaying the blurred image (16) on an image display (36); (ii) manually identifying an image patch (25) that includes the captured light trail (24) in the displayed blurred image (16); (iii) calculating a point spread function for the captured light trail (24) with a control system (28); and (iv) deblurring at least a portion of the blurred image (16) with the control system (28) utilizing the calculated point spread function.