Abstract:
A pair of images subjected to image processing is divided. Next, based on mutually-corresponding divided images, mutually-corresponding matching images are respectively set. When a corresponding point of a characteristic point in one matching image is not extracted from the other matching image, adjoining divided images are joined together, and based on the joined divided image, a new matching image is set.
Abstract:
Improving stereo matching speed and accuracy, an image data input unit acquires image data of plural images of a predetermined region captured from plural different positions. A reference disparity setting unit sets a reference disparity suitable for the plural images. The search range setting unit sets a predetermined range smaller than the image range as a search range for stereo matching, by referring to points in the images between which the reference disparity set by the reference disparity setting unit is provided. A stereo matching unit searches out, for an arbitrary point in one of the plural images, a point in the other image that matches the arbitrary point, from the search range set by the search range setting unit, by referring to a point in the other image that provides the reference disparity set by the reference disparity setting unit.
Abstract:
A stereo image processing apparatus 1 specifies a line pair having a high correlation between one image and the other image of a stereo image, for an image region which has a predetermined width and is parallel to a scanning direction (X direction) in a stereo image which shoots a predetermined region from two different positions and has a scanning line direction and an epipolar line direction matched with each other, obtains a shift (vertical azimuth difference) in a vertical direction (Y direction) between the one image and the other image of the stereo image according to each position of the specified line pair, and corrects the stereo image so as to eliminate the obtained shift.
Abstract:
To improve stereo matching speed and accuracy. An image data input unit 10 acquires image data of plural images of a predetermined region captured from plural different positions. A reference disparity setting unit 12 sets a reference disparity suitable for the plural images. The search range setting unit 13 sets a predetermined range smaller than the image range as a search range for stereo matching, by referring to points in the images between which the reference disparity set by the reference disparity setting unit 12 is provided. A stereo matching unit 11 searches out, for an arbitrary point in one of the plural images, a point in the other image that matches the arbitrary point, from the search range set by the search range setting unit 13, by referring to a point in the other image that provides the reference disparity set by the reference disparity setting unit 12.
Abstract:
To correctly associate coinciding positions between a plurality of images.In a case where an operator makes an operation of inputting associated supplementary lines A2 and A1 into left and right images respectively, and associated supplementary lines B2 and B1 into the left and right images respectively, stereo matching processing system associates coordinate a2 of intersection of a scanning line and supplementary line A2 in the left image with coordinate al of intersection of the scanning line and supplementary line A1 in the right image on search plane, and coordinate b2 of intersection of the scanning line and supplementary line B2 in the left image with coordinate b1 of intersection of the scanning line and supplementary line B1 in the right image on search plane. Hence, the stereo matching processing system 1 can redress wrong associations on search plane and correctly associate coinciding positions in the left and right images.
Abstract:
A stereo matching processing system includes an associating unit that associates with each other such regions, in a plurality of images obtained by shooting a same object from different directions, that are on a same scanning line and have a largest correlation coefficient between them, as items that represent a same position, and a line segment determining unit that determines whether or not line segments that are associated with each other as items that teach a same position are drawn in the plurality of images respectively. When said line segment determining unit determines that the line segments are drawn, said associating unit associates with each other, not such regions that are on the same scanning line and have a largest correlation coefficient between them, but intersections at which the scanning line and the line segments each cross, as items that represent a same position.
Abstract:
A three-dimensional topographical data precision improving device (10) removing noise that occurs in water regions of three-dimensional topographical data comprises a water region specifying unit (13) specifying the range of any one water region; a feature extraction unit (14) extracting feature values within any one water region that describe altitude distribution pattern of each local region in the three-dimensional topographical data; a segmentation unit (15) segmenting the whole range into candidate water regions and non-water regions by comparing the feature values of the specified water region with those of each point in the three-dimensional topographical data; a water region extraction unit (16) extracting water regions from the candidate water regions; and a plane creation unit (17) creating a corrected plane of each water region using the altitudes of the surrounding non-water regions and replacing the water region extracted by the water region extraction unit (16) with the corrected plane.
Abstract:
A three-dimensional topographical data precision improving device (10) removing noise that occurs in water regions of three-dimensional topographical data comprises a water region specifying unit (13) specifying the range of any one water region; a feature extraction unit (14) extracting feature values within any one water region that describe altitude distribution pattern of each local region in the three-dimensional topographical data; a segmentation unit (15) segmenting the whole range into candidate water regions and non-water regions by comparing the feature values of the specified water region with those of each point in the three-dimensional topographical data; a water region extraction unit (16) extracting water regions from the candidate water regions; and a plane creation unit (17) creating a corrected plane of each water region using the altitudes of the surrounding non-water regions and replacing the water region extracted by the water region extraction unit (16) with the corrected plane.
Abstract:
Provided is a flight obstacle extraction device, a flight obstacle extraction method, and a recording medium which attain the detailed extraction of flight obstacles with fewer man-hours. An altitude information acquisition unit (20) receives a plurality of images imaging a predetermined area from a plurality of different positions, and generates digital surface model data expressing the surface of the given area with three-dimensional coordinates. An obstacle candidate computation unit (50), on the basis of generated digital surface model data, extracts candidates for flight obstacles which may conflict with a flight restriction surface from the images. A flight obstacle determination unit (60) detects flight obstacles conflicting with the flight restriction surface from among the candidates for flight obstacles extracted by the obstacle candidate computation unit (50). s for flight obstacles.
Abstract:
A change discrimination device capable of discriminating an alteration of a photographing target only from an aerial photograph or irrespectively of a difference in lighting conditions or photographing conditions at the time of taking a photo, and at minute distance intervals on a pixel basis, which receives input of a plurality of aerial image data at a new time point and an old time point, generates three-dimensional data (DSM) by subjecting the applied aerial image data to stereo-matching processing, generates ortho-image data and ortho-DSM data by normalizing the aerial image data and the generated DSM data, compares colors by using the generated ortho-image of the new time point and ortho-image of the old time point and compares heights by using the generated ortho-DSM data of the new time point and ortho-DSM data of the old time point to discriminate an alteration of a feature on the earth.