Abstract: An electronic device, method, and computer readable medium for compositing high dynamic range frames are provided. The electronic device includes a camera, and a processor coupled to the camera. The processor registers the plurality of multi-exposure frames with a hybrid of matched features to align non-reference frames with a reference frame; generates blending maps of the plurality of multi-exposure frames to reduce moving ghost artifacts and identify local areas that are well-exposed in the plurality of multi-exposure frames; and blends the plurality of multi-exposure frames weighted by the blending maps using a two-step weight-constrained exposure fusion technique into a high dynamic range (HDR) frame.

Abstract: A method and device for acquiring a target object, and a robot are provided. The method includes: acquiring a plurality of frames of continuous images in video images, where each frame of image includes a first target object; acquiring, based on the continuous images including the first target object, a first target image from which a background has been removed; acquiring, based on a distance from a first center point of the first target image to a common boundary, a location of a second target object in the first target image, where the first center point is determined based on a color of the second target object, the common boundary is an overlapping boundary of the second target object and the first target object, and the second target object is included in the first target object; and extracting the second target object based on the location of the second target object in the first target image.

Abstract: A method and apparatus of image stitching using confidence level of image matching on image pair to be stitched are disclosed. According to the present invention, the first quality of image matching is determined for a current image based on feature matching on first image pairs corresponding to the current image and a neighboring image set. If the first quality of image matching for at least one first image pair satisfies a first quality criterion, then the second quality of image matching is determined based on pixel-domain matching for one or more candidate image pairs, where each candidate image pair has a corresponding first quality of image matching satisfying the first quality criterion. If the second quality of image matching for a candidate image pair satisfies a second quality criterion, then the matched image pair is stitched.

Abstract: A control method for an image processing apparatus that generates a plurality of pieces of album data corresponding to a plurality of albums includes automatically selecting at least one piece of image data out of a plurality of pieces of image data as common image data corresponding to an image to be placed in a common page, which is a page common to all of the plurality of albums, based on an evaluation that is based on a first factor, and automatically selecting at least one piece of image data out of the plurality of pieces of image data as individual image data corresponding to an image to be placed in an individual page, which is a page not common to all of the plurality of albums, based on an evaluation that is based on a second factor.

Abstract: A digital graduated filter is implemented in an imaging device by combining multiple images of the subject wherein the combining may include combining different numbers of images for highlights and for shadows of the subject. The imaging device may present a user with a set of pre-defined graduated filter configurations to choose from. A user may also specify the direction of graduation and strength of graduation in a viewfinder. In an alternative implementation, combining may include scaling of pixels being added instead of varying the number of images being combined. In an alternative implementation, the combining of multiple images may include combining a different number of images for highlights of the subject than for shadows of subject.

Abstract: A method and apparatus for constructing a 3D scene model are provided. The method includes: acquiring a first point cloud corresponding to a current target scene (S101); determining a first partial point cloud corresponding to a dynamic object from the first point cloud (S102); constructing a foreground 3D model based on the first partial point cloud (S103); and superimposing the foreground 3D model with a background 3D model to obtain a current 3D scene model (S104). As can be seen, it is not necessary to fuse each pixel acquired by each depth camera. Instead, the dynamic object is determined in the point cloud acquired by the depth camera. Only the foreground 3D model corresponding to the dynamic object is superimposed with the background 3D model corresponding to the static objects obtained in advance. This reduces the amount of computation to build a 3D scene model.

Abstract: A system control unit sets at least one of a non-overlapped area in which an nth image and an (n+1)st image do not overlap and a low contrast area of the (n+1)st image as an in valid area that is not used for misalignment detection of the (n+1)st image. Then, the system control unit sets alignment small blocks for a motion vector search in only an area excluding the invalid area in the overlapped area in which two combining target images overlap.

Abstract: Methods, apparatus, and processor-readable storage media for dynamic digital information retrieval are provided herein. An example computer-implemented method includes training a machine learning object detection model using server component images and one or more features of the server component images; determining a type of server device captured by at least one camera-derived input, wherein determining the type of server device comprises analyzing the at least one camera-derived input using the machine learning object detection model; identifying one or more server components captured by the at least one camera-derived input by analyzing, within a context of the determined type of server device, the at least one camera-derived input using the machine learning object detection model; and outputting, to at least one display, information pertaining to the identified server components, wherein the information is retrieved from a data source related to the determined type of server device.

Abstract: An attitude estimation apparatus (30) includes: a data acquiring unit (32) for acquiring observation data; a range-measurement point coordinate calculator (33A) for calculating geodetic coordinates of a range-measurement point in a geodetic coordinate system using positioning data, ranging data, actual attitude data, and an estimated value of an unknown parameter representing an attitude of a flying object; an image coordinate calculator (33B) for calculating coordinates of a projected point by performing projection transformation from the geodetic coordinate system to an image coordinate system on the geodetic coordinates; an image matching processor (34) for detecting image coordinates of the range-measurement point appearing in a first captured image by executing image matching between the first captured image and a second captured image selected from captured images; and an attitude estimator (35) for correcting the estimated value such that a magnitude of a difference between the coordinates of the proje

Abstract: A method may include acquiring, via a capture system, a dataset associated with a user at a first location, detecting, via a control system, the user at a second location, displaying, via an environmental system, one or more images generated from the dataset at the second location in response to detecting the user at or past the second location, and triggering, via a special effect system, a special effect during the displaying at the second location in response to detecting the user at or past the second location. The dataset may include image data of the user.

Abstract: An image processing method and apparatus, a storage medium and an electronic device are disclosed. The method comprises: acquiring a first face image in a real scene and a second face image in a virtual scene, wherein the second face image is generated at least according to a first value of at least one target parameter, and the at least one target parameter is used for determining at least one attribute of a face image in the virtual scene; extracting at least one first image feature from the first face image, and extracting at least one second image feature from the second face image; acquiring a similarity between the at least one first image feature and the at least one second image feature; adjusting the first value of the at least one target parameter based on the similarity to obtain a target value of the at least one target parameter; and rendering the at least one target parameter according to the target value to obtain the target face image in the virtual scene.

Abstract: An image processing system includes an image obtaining unit that obtains images based on capturing from plural directions by plural cameras, an information obtaining unit that obtains viewpoint information indicating a virtual viewpoint, and a generation unit configured to generate virtual viewpoint images on a basis of the obtained images and viewpoint information. The generation unit generates a first virtual viewpoint image outputted to a display apparatus that displays an image for a user to specify a virtual viewpoint and a second virtual viewpoint image outputted to an output destination different from the display apparatus by using at least one of data generated in a process for generating the first virtual viewpoint image by image processing using the plural images obtained by the image obtaining unit and the first virtual viewpoint image, the second virtual viewpoint image having a higher image quality than that of the first virtual viewpoint image.

Abstract: A three-dimensional imaging system for generating a 3D panoramic video/image is disclosed. The three-dimensional imaging system includes a plurality of stereoscopic pairs of compound cameras which are separated by a predefined distance d. The imaging system is configured to operate in a first mode to generate panoramic images simultaneously using the compound cameras. Spatial distortion and temporal distortion are calculated for each column in a region of overlap of the field of view of the panoramic images generated. The column for which the spatial and temporal distortion is minimum is marked as a seam location. The marked seam location is changed based on location of a motion in the column for which the calculated spatial and temporal distortion is minimum.

Abstract: Generating thumbnails from panoramic images is described. In one or more implementations, a 2D projection of a panoramic image is received and projected onto a 3D surface to generate a 3D projection. Portions of the 3D projection are formed, and each portion is projected to a 2D plane to generate 2D projections of the portions. Object recognition is then performed on the portions that identifies objects, attributes of the objects, and locations of the objects within the panoramic image. Responsive to an image search query matching one of the recognized objects, the system generates a thumbnail from the panoramic image specific to a portion of the panoramic image that contains the object and outputs the thumbnail.

Abstract: A method of localizing an object includes capturing a first image of the object from a first camera position, performing edge detection on the first image to form an edge-detected second image, and performing a distance transform on the second image to form a distance transformed third image. A virtual camera is positioned in virtual space relative to a virtual model of the object, and an edge-detected fourth image of the virtual model of the object is generated. An alignment cost is generated of the edge-detected fourth image of the virtual model relative to the edge-detected second image of the object, and a position of the virtual camera is transformed to a position having a lower alignment cost than the alignment cost. A physical location of the object is estimated based on the transformed virtual camera position.

Abstract: A system is provided for identifying damages of a vehicle. During operation, the system can obtain a set of digital images associated with a set of tagged digital images as training data. Each tagged digital image in the set of tagged digital images may include at least one damage object. The system can train a damage identification model based on the training data. When training the damage identification model, the system may identify at least a damage object in the training data based on a target detection technique. The system may also generate a set of feature vectors for the training data. The system can use the set of feature vectors to optimize a set of parameters associated with the damage identification model to obtain a trained damage identification model. The system can then apply the trained damage identification model to obtain a damage category prediction result.

Abstract: A method of decoding a bitstream by an electronic device is provided. An image frame is received from the bitstream. A block unit is determined from the received image frame. A plurality of model parameters is derived based on motion information of a plurality of neighboring blocks neighboring the block unit. An intermediate block is derived for a sub-block in the block unit based on the plurality of model parameters. A vector formula is determined based on the plurality of model parameters, and at least one vector value is calculated based on the vector formula for at least one sampling position in the sub-block. The at least one vector value is compared with a threshold to determine whether the intermediate block is adjusted based on the vector formula to generate a predicted block. The sub-block is reconstructed based on the predicted block.

Abstract: The present disclosure relates to a method for removing an object to be processed from an image and a device for performing the method. A method for removing an object to be processed from an image can comprise the step of: an image processing device deciding an object to be processed in an image; and the image processing device performing image post-processing with respect to the object to be processed, wherein the object to be processed can be an object which is unintentionally captured.

Abstract: An automated process empirically normalizes a “dark” image by adjusting the apparent exposure to compensate for nonlinearity in the luminance response of the image sensor. The process includes receiving at least two digital images, one of the digital images having an exposure value that is greater than that of another of the digital images. A reduced-resolution pair of images is produced from the at least two digital images. At least one representative scale factor is calculated from tonal values in the two images and at least one empirical scale factor is determined by selective interpolation between the representative scale factor and a comparative scale factor. The empirical scale factor is used in a function applied pixelwise to the darker of the digital images to produce an empirically normalized digital image.

Abstract: Systems and methods are disclosed for image signal processing. For example, methods may include receiving, by an image signal processor, one or more input image signals from one or more image sensors; determining a mapping based on the input image signal(s), wherein the mapping includes records that associate image portions of an output image with corresponding image portions of the input image signal(s); sorting the records of the mapping according to an order of the corresponding image portions of the input image signal(s); applying, by the image signal processor, image processing to image portions of the input image signal(s) to determine image portions of one or more processed images in the order; and determining, by the image signal processor, the image portions of the output image based at least in part on the mapping and the corresponding image portions of the processed image(s) in the order.

Abstract: Methods, apparatus, systems, and computer program products for displaying captured screenshots are disclosed herein. One method includes capturing, by an information handling device, a set of screenshots of a main display screen of a computing device and displaying the captured set of screenshots on a sub-display screen of the computing device. Apparatus, systems, and computer program products that include and/or perform the methods are also disclosed herein.

Abstract: A method and a fault-tolerant computer architecture (FCTA) for fail-safe trajectory planning for a moving entity (MOV). The method and FCTA uses a commander (COM), a monitor (MON), and a safe envelope generating stage (ENV). Based on sensor input, the commander (COM) and the monitor (MON) produce real-time images of objects (OBJ1, OBJ2) detected. A trajectory planning stage (TRJ-PLN) generates trajectories (COM-TRJ1, COM-TRJ2), and the safe envelope generating stage (ENV) generates a safety envelope. The commander (COM) provides the one or more trajectories (COM-TRJ1, COM-TRJ2) to the monitor (MON) and the decision subsystem (DECIDE). A trajectory verification stage (TRJ-VRFY) verifies a trajectory (COM-TRJ1, COM-TRJ2) generated by the commander (COM) only if said trajectory (COM-TRJ1, COM-TRJ2) is completely located inside said safety envelope. A moving entity (MOV) uses a trajectory (COM-TRJ1, COM-TRJ2) generated by the commander (COM) only when said trajectory is verified by the monitor (MON).

Abstract: A method performed by a vehicle system for handling images of the surroundings of a vehicle. An image of the surroundings of the vehicle is obtained. The image is obtained from at least one side image capturing device mounted in or on the vehicle, and the image capturing device comprises a fisheye camera lens. At least a part of the distortions in the image is corrected to obtain a corrected image. The corrected image is rotationally transformed using a first rotational transformation to obtain a first transformed image. The corrected image is rotationally transformed using a second rotational transformation to obtain a second transformed image. The first and second transformed images are consecutive or adjacent images.

Abstract: A system for assembling a group composite image from individual subject images is described. Often subjects of a group vary in height. Additionally, as each subject is photographed individually, different zoom factors can be applied by a camera that affects a pixel density of the image captured. The system includes a fiducial marking device that emits collimated light to form one or more fiducial markers on a subject while an image is captured by the camera. Based on a location of the fiducial markers in the image, a pixel density of the image and a reference height of the subject can be determined. The individual subject image can be scaled based on the pixel density and reference height to account for the varying subject heights and zoom factors to generate a group composite image that accurately represents the subjects of the group relative to one another.

Abstract: The method of analyzing a difference of at least two gradings of an image on the basis of: obtaining a first graded picture (LDR) with a first luminance dynamic range; obtaining data encoding a grading of a second graded picture (HDR) with a second luminance dynamic range, different from the first luminance dynamic range; determining a grading difference data structure (DATGRAD) on the basis of at least the data encoding the grading of the second graded picture (HDR), allows more intelligently adaptive encoding of the imaged scenes, and consequently also better use of those pictures, such as higher quality rendering under various rendering scenarios.

Abstract: This invention discloses a system and method for detection of foreign object debris (FOD) on the areas of including but not limited to the airport runways, taxiways, aprons and adjacent areas. The invention makes use of single or multiple passive optical sensors monitoring the areas for signal acquisition, a database and a processing unit to further analyze the captured optical signal in order to detect the presence; and in case of the detection of the foreign debris in various threat levels, creating an alert for the removal thereof; depending on variables such as the estimated area and foreign object size and visual characteristics.

Abstract: The present subject matter provides a technical solution for various technical problems associated with precision agriculture imagery. A technical solution for stitching together successive passes of captured images may include using multiple image capture devices, where the image capture devices have different fields of view. A first camera may be used to provide a first field of view (FOV), and may be configured to provide a selected ground sample distance (GSD) for precision agriculture imagery analysis. A second camera may be used to provide a wider FOV, and may be used to provide sufficient stitching process overlap between images captured in successive passes.

Abstract: An image processing apparatus includes an acquisition unit configured to acquire a panoramic image, and a moving image generation unit configured to generate a moving image based on the panoramic image, the moving image generation unit configured to crop the panoramic image by sequentially moving a position of a cropping area for cropping the panoramic image, thereby generating a moving image in which a plurality of cropped images cropped by changing the position of the cropping area is sequentially reproduced, wherein according to an aspect ratio or a size in a predetermined direction of the panoramic image, the moving image generation unit switches whether to crop the panoramic image with a predetermined aspect ratio or crop the panoramic image with an aspect ratio different from the predetermined aspect ratio.

Abstract: An image stitching method applied to a monitoring camera apparatus with a first image receiver and a second image receiver for acquiring a first image and a second image. The image stitching method includes detecting a plurality of first features in the first image and a plurality of second features in the second image, dividing the plurality of first features at least into a first group and a second group and further dividing the plurality of second features at least into a third group, analyzing the plurality of first features and the plurality of second features via an identification condition to determine whether one of the first group and the second group is matched with the third group, and utilizing two matched groups to stitching the first image and the second image.

Abstract: A control device including a main subject detection unit that detects a first main subject from among subjects included in a first image, and acquires main subject information indicating the first main subject, a distance information calculation unit that detects a distance of a subject included in a first image, and acquires first distance information indicating the distance, and a detection unit that detects a distance within which a first main subject is included on the basis of main subject information and first distance information, and acquires main subject distance information indicating the distance within which the first main subject is included.

Abstract: Systems and techniques are disclosed for automatically creating a group shot image by intelligently selecting a best frame of a video clip to use as a base frame and then intelligently merging features of other frames into the base frame. In an embodiment, this involves determining emotional alignment scores and eye scores for the individual frames of the video clip. The emotional alignment scores for the frames are determined by assessing the faces in each of the frames with respect to an emotional characteristic (e.g., happy, sad, neutral, etc.). The eye scores for the frames are determined based on assessing the states of the eyes (e.g., fully open, partially open, closed, etc.) of the faces in individual frames. Comprehensive scores for the individual frames are determined based on the emotional alignment scores and the eye scores, and the frame having the best comprehensive score is selected as the base frame.

Abstract: An image processing apparatus includes a control portion and an output portion. The control portion sets a letter included in a document as a target letter, and performs connection processing of connecting the target letter and a next letter to each other with a connection line without changing the font of the target letter and without changing the font of the next letter, the next letter being a letter positioned immediately after the target letter in order of alignment in a writing direction. The output portion outputs the document after the connection processing is performed on the document.

Abstract: A face image de-identification apparatus and method are disclosed. The face image de-identification apparatus may include an emoji generator configured to generate a first emoji image including facial feature information corresponding to a face image using the face image stored in a database, and an image inserter configured to insert the first emoji image into the database by replacing the first emoji image with the face image.

Abstract: This disclosure provides an image processing method, an electronic device and a non-transitory computer-readable storage medium, and relates to the field of image processing technique. The image processing method and apparatus and the electronic device provided by this application perform denoising on the to-be-processed image to obtain a denoised image, and then perform detail enhancement on the target area image extracted from the denoised image to obtain a detail enhanced image, thereafter fuse the denoised image with the detail enhanced image to obtain an output image. Since detail enhancement has been performed on the target area image, the obtained output image is sharper and the display effect is better.

Abstract: A camera system and method provide a trailing motion blur effect without the use of a flash. In one embodiment, a variable light-transmissive filter is positioned in front of an image sensor. While the light-transmissive property of the filter is lower, the blurred image of the object in motion is produced. The light-transmissive property of the filter is increased during the exposure in order to produce a clearer image of the object. In a method, a plurality of images taken in rapid succession are combined to produce a clear image of the object with a trailing blurred image of the object.

Abstract: The present invention discloses a method and device for storing image data, the method includes: receiving image data to-be-stored; extracting basic information of the image data and generating a header file; partitioning the image data by a preset block size according to the basic information of the image data, and generating a data file; and storing the header file and the data file and generating a storage file. In the present invention, image data are stored as double files, so as to add basic information of an image into the image, and in storing a massive-data image, the image is partitioned by a preset size prior to sequential storage, so that when the image is displayed, only one or several sub-blocks of the image are extracted and displayed, allowing quick display of the image with massive data, improving the efficiency of image display.

Abstract: An image processing apparatus, an image capturing system, an image processing method, and a recording medium are provided.

Abstract: A method of multi-sensor alignment includes mechanically moving at least one sensor in a plurality of sensors to boresight and focus the plurality of sensors with one another so a respective optical center of each of the plurality of sensors is aligned and focused. The method includes collecting calibration images of a target wherein each sensor of the plurality of sensors collects at least one image of the target, and analytically comparing the images with one another to produce a look up table (LUT) of optical distortion and spatial registration for registration of image data from the plurality of sensors. The method includes saving the LUT in sensor memory for use in registering live images from the plurality of sensors.

Abstract: An image processing apparatus according to an example embodiment includes a storage unit configured to store a relative position and an angle of each of a plurality of radiation detection apparatuses attached to a platform in first imaging and a composition unit configured to, on the basis of the relative position and angle of each of the radiation detection apparatuses which are stored in the storage unit, combine a plurality of images obtained by a plurality of radiation detection apparatuses in second imaging subsequent to the first imaging.

Abstract: An obtainment unit obtains a captured image captured by an image capturing unit. A control unit sets, as a distribution target image which is to be distributed, an image of a partial region cut out from the captured image or an image obtained by capturing the partial region by controlling at least one of panning, tilting, and zooming of the image capturing unit, and, based on one of a distribution frame rate of the distribution target image and a set time period for distributing the distribution target image, controls the other of the distribution frame rate and the set time period. The distribution target image is distributed for the set time period in accordance with the distribution frame rate.

Abstract: An example system for generating stereoscopic light field panoramas includes a receiver to receive a plurality of synchronized images. The system also includes a calibrator and projector to calibrate the synchronized images, undistort the synchronized images, and project the undistorted images to a sphere to generate undistorted rectilinear images. The system further includes a disparity estimator to estimate a disparity between neighboring views of the undistorted rectilinear images to determine an optical flow between the undistorted rectilinear images. The system includes a view interpolator to perform in-between view interpolation on the undistorted rectilinear images based on the optical flow. The system also further includes a light field panorama generator to generate a stereoscopic light field panorama for a plurality of perspectives using concentric viewing circles.

Abstract: A system and method is provided for using rules to perform a set of actions on video data when conditions are satisfied by the video data. The system receives rules to select a theme, portions of the video data and/or a type of output. For example, based on annotation data associated with the video data, the system may apply rules to select one or more themes, with each of theme associated with a portion of the video data. In some examples, the system may apply rules to determine the portion of the video data associated with the theme. The system may apply rules to generate various types of output data associated with each of the selected themes, the types of output data may include a video summarization, individual video clips, individual video frames, a photo album including video frames selected from the video data or the like.

Abstract: An image system includes processing circuitry. The processing circuitry captures an image captured by a device such as a camera, and detects an attitude of the device. The processing circuitry corrects the captured image based on the attitude of the device and a designation including a point on the image and at least one of a region of the image and a direction.

Abstract: Provided is a method of spatially referencing a plurality of images captured from a plurality of different locations within an indoor space by determining the location from which the plurality of images was captured. The method may include obtaining a plurality of distance-referenced panoramas of an indoor space. The distance-referenced panoramas may each include a plurality of distance-referenced images each captured from one position in the indoor space and at a different azimuth from the other distance-referenced images, a plurality of distance measurements, and orientation indicators each indicative of the azimuth of the corresponding one of the distance-referenced images. The method may further include determining the location of each of the distance-referenced panoramas based on the plurality of distance measurements and the orientation indicators and associating in memory the determined locations with the plurality of distance-referenced images captured from the determined location.

Abstract: The present disclosure relates to an image processing apparatus and an image processing method that make it possible to generate a texture image of high picture quality at a predetermined viewpoint using an omnidirectional image. A plurality of real cameras image a plurality of reference images at a plurality of viewpoint positions in a plurality of sight line directions. A great weight is applied to a reference image in a sight line direction close to a virtual viewpoint specified in response to a movement of a head mounted display and having a virtual viewpoint position and a sight line direction to generate a virtual viewpoint image by weighted averaging, and the virtual viewpoint image is displayed on the head mounted display. The present disclosure can be applied, for example, to a home server or the like that generates a display image of a predetermined viewpoint from an omnidirectional image.

Abstract: An image processing unit generates a corrected bird's-eye-view image that is a captured bird's-eye-view image and that is a bird's-eye-view image from which irradiation light present in the captured image has been removed. The corrected bird's-eye-view image is generated as a bird's-eye-view image representing a difference between the captured bird's-eye-view image and a difference image that is an image representing a change in a pixel value of the captured bird's-eye-view image. The image processing unit generates a corrected history image that is a bird's-eye-view image obtained by combining the corrected bird's-eye-view images while shifting positions of the corrected bird's-eye-view images on the basis of a movement amount of the own vehicle. The image processing unit generates a corrected display image that is a bird's-eye-view image obtained by combining the corrected history image and the latest captured bird's-eye-view image, and makes a display unit display the corrected display image.

Abstract: One embodiment of the present disclosure presents a technique for generating an augmented reality effect. The technique includes receiving first input data including an image of a face. The technique further includes, based on the first input data, generating a first intermediate texture corresponding to an eyelid of the face with make-up. The technique further includes, based on the first input data, generating a second intermediate texture corresponding to the eyelid of the face without make-up. The technique also includes generating an output texture based on the first intermediate texture and the second intermediate texture. The technique further includes generating an effect by applying the output texture to second input data corresponding to a second image of a second face.

Abstract: A vehicular vision system includes a camera, a distance sensor and a controller having at least one processor, where image data captured by the camera and sensor data captured by the distance sensor are processed at the controller. The controller, responsive to processing of captured image data and of captured sensor data, detects an object. The controller determines the distance to the detected object based at least in part on difference between the positions of the detected object in captured image data and in captured sensor data. The controller, responsive to processing of captured image data and of captured sensor data, and responsive to the determined distance to the detected object, determines that the detected object represents a collision risk. The controller informs a driver of the vehicle of the collision risk and/or controls the vehicle to mitigate the collision risk.

Abstract: Captured images acquired by a plurality of imaging units are output to a captured image combining unit, which generates a composite image by joining the captured images in accordance with composite setting information generated by a composite setting information generation unit. A specific region information generation unit generates specific region information indicating the specific region corresponding to a specific imaging region in the composite image. In accordance with the specific region information, the captured image combining unit can easily perform an invalidation or emphasizing process, for example, on the image corresponding to the specific imaging region. The specific region information is also associated with the composite image generated by the captured image combining unit, so that reproduction control on the specific region corresponding to the specific imaging region in the composite image can be performed at the time of reproduction or the like of the composite image.

Abstract: A method of obtaining image data includes scanning an imaging area with an imaging device while obtaining multiple overlapping images of the imaging area. The method also includes transforming the overlapping images by performing frame averaging on the overlapping images to produce at least one enhanced image of the imaging area.