Abstract: A sensor arrangement including at least one electro-optical sensor which is secured to a receiving structure of a sensor holder. The electro-optical sensor includes a sensor housing with an optically active sensor layer that is arranged thereon. The optically active sensor layer forms a light-sensitive plane. The sensor holder includes a non-adjustable receiving structure which compensates for a previously determined deviation in shape of the electro-optical sensor from a desired shape.

Abstract: Examples of the present disclosure describe systems and methods for capturing data to acquire indoor and outdoor geometry. In aspects, a data capture system may be configured to acquire texture data, geometry data, navigation data and/or orientation data to support geolocation and georeferencing within indoor and outdoor environments. The data capture system may further be configured to acquire seamless texture data from a 360° horizontal and vertical perspective to support panoramic video and images.

Abstract: Examples of the present disclosure describe systems and methods for capturing data to acquire indoor and outdoor geometry. In aspects, a data capture system may be configured to acquire texture data, geometry data, navigation data and/or orientation data to support geolocation and georeferencing within indoor and outdoor environments. The data capture system may further be configured to acquire seamless texture data from a 360° horizontal and vertical perspective to support panoramic video and images.

Abstract: Examples of the present disclosure describe systems and methods for capturing data to acquire indoor and outdoor geometry. In aspects, a data capture system may be configured to acquire texture data, geometry data, navigation data and/or orientation data to support geolocation and georeferencing within indoor and outdoor environments. The data capture system may further be configured to acquire seamless texture data from a 360° horizontal and vertical perspective to support panoramic video and images.

Abstract: Mobile platforms are used to capture an area using a variety of sensors (e.g., cameras and laser scanners) while traveling through the area, in order to create a representation (e.g., a navigable set of panoramic images, or a three-dimensional reconstruction). However, such sensors are often precisely calibrated in a controlled setting, and miscalibration during travel (e.g., due to a physical jolt) may result in a corruption of data and/or a recalibration that leaves the platform out of service for an extended duration. Presented herein are techniques for verifying sensor calibration during travel. Such techniques involve the identification of a sensor path for each sensor over time (e.g., a laser scanner path, a camera path, and a location sensor path) and a comparison of the paths, optionally after registration with a static coordinate system, to verify that the continued calibration of the sensors during the mobile operation of the platform.

Abstract: Examples of the present disclosure describe systems and methods for capturing data to acquire indoor and outdoor geometry. In aspects, a data capture system may be configured to acquire texture data, geometry data, navigation data and/or orientation data to support geolocation and georeferencing within indoor and outdoor environments. The data capture system may further be configured to acquire seamless texture data from a 360° horizontal and vertical perspective to support panoramic video and images.

Abstract: Mobile platforms are used to capture an area using a variety of sensors (e.g., cameras and laser scanners) while traveling through the area, in order to create a representation (e.g., a navigable set of panoramic images, or a three-dimensional reconstruction). However, such sensors are often precisely calibrated in a controlled setting, and miscalibration during travel (e.g., due to a physical jolt) may result in a corruption of data and/or a recalibration that leaves the platform out of service for an extended duration. Presented herein are techniques for verifying sensor calibration during travel. Such techniques involve the identification of a sensor path for each sensor over time (e.g., a laser scanner path, a camera path, and a location sensor path) and a comparison of the paths, optionally after registration with a static coordinate system, to verify that the continued calibration of the sensors during the mobile operation of the platform.

Abstract: Mobile platforms are used to capture an area using a variety of sensors (e.g., cameras and laser scanners) while traveling through the area, in order to create a representation (e.g., a navigable set of panoramic images, or a three-dimensional reconstruction). However, such sensors are often precisely calibrated in a controlled setting, and miscalibration during travel (e.g., due to a physical jolt) may result in a corruption of data and/or a recalibration that leaves the platform out of service for an extended duration. Presented herein are techniques for verifying sensor calibration during travel. Such techniques involve the identification of a sensor path for each sensor over time (e.g., a laser scanner path, a camera path, and a location sensor path) and a comparison of the paths, optionally after registration with a static coordinate system, to verify that the continued calibration of the sensors during the mobile operation of the platform.

Abstract: Many imaging scenarios involve an achromatic image (e.g., a panchromatic image or a near-infrared image) and one or more concurrently captured monochromatic images (e.g., RGB images captured through a Bayer filter array), and the compositing of these images through de-mosaicing and/or pan-sharpening to generate a high-resolution color image. However, in many such scenarios, the monochromatic images may exhibit distortion of edge geometry, resulting in artifacts and/or color distortions near visual edges of the composite image. However, such distortions may be absent from the achromatic image, and edge geometry may be represented as an intensity gradient among respective neighborhoods of achromatic pixels. Presented herein are techniques for reducing such distortions in monochromatic images through iterative adjustment of monochromatic pixel intensity to reflect the gradients of the neighborhoods of the corresponding achromatic pixels.

Abstract: Mobile platforms are used to capture an area using a variety of sensors (e.g., cameras and laser scanners) while traveling through the area, in order to create a representation (e.g., a navigable set of panoramic images, or a three-dimensional reconstruction). However, such sensors are often precisely calibrated in a controlled setting, and miscalibration during travel (e.g., due to a physical jolt) may result in a corruption of data and/or a recalibration that leaves the platform out of service for an extended duration. Presented herein are techniques for verifying sensor calibration during travel. Such techniques involve the identification of a sensor path for each sensor over time (e.g., a laser scanner path, a camera path, and a location sensor path) and a comparison of the paths, optionally after registration with a static coordinate system, to verify that the continued calibration of the sensors during the mobile operation of the platform.

Abstract: Many imaging scenarios involve an achromatic image (e.g., a panchromatic image or a near-infrared image) and one or more concurrently captured monochromatic images (e.g., RGB images captured through a Bayer filter array), and the compositing of these images through de-mosaicing and/or pan-sharpening to generate a high-resolution color image. However, in many such scenarios, the monochromatic images may exhibit distortion of edge geometry, resulting in artifacts and/or color distortions near visual edges of the composite image. However, such distortions may be absent from the achromatic image, and edge geometry may be represented as an intensity gradient among respective neighborhoods of achromatic pixels. Presented herein are techniques for reducing such distortions in monochromatic images through iterative adjustment of monochromatic pixel intensity to reflect the gradients of the neighborhoods of the corresponding achromatic pixels.

Abstract: Apparatuses and methods for enhancing a “primary” large format, digital, macro-image with “secondary” image data are provided. The secondary image data is collected utilizing one or more secondary optical systems having at least one electro-optical detector array (e.g., a CCD array) and a specific set of optical mirrors or optical prisms, arranged in such a way that the secondary optical systems extend the angular field-of-view of the primary optical system and the resultant digital image in at least two opposing directions, for instance, in the left and right and/or fore and aft directions. The primary image data and the secondary image data may be distinct and/or may include portions that overlap with one another. Further, the primary image data and the secondary image data may be collected at the same or different resolutions. The collected primary image data and secondary image data are utilized to generate a single output image.

Abstract: Apparatuses and methods for enhancing a “primary” large format, digital, macro-image with “secondary” image data are provided. The secondary image data is collected utilizing one or more secondary optical systems having at least one electro-optical detector array (e.g., a CCD array) and a specific set of optical mirrors or optical prisms, arranged in such a way that the secondary optical systems extend the angular angle-of-view of the primary optical system and the resultant digital image in at least two opposing directions, for instance, in the left and right and/or fore and aft directions. The primary image data and the secondary image data may be distinct and/or may include portions that overlap with one another. Further, the primary image data and the secondary image data may be collected at the same or different resolutions. The collected primary image data and secondary image data are utilized to generate a single output image.

Abstract: Apparatuses and methods for enhancing a “primary” large format, digital, macro-image with “secondary” image data are provided. The secondary image data is collected utilizing one or more secondary optical systems having at least one electro-optical detector array (e.g., a CCD array) and a specific set of optical mirrors or optical prisms, arranged in such a way that the secondary optical systems extend the angular field-of-view of the primary optical system and the resultant digital image in at least two opposing directions, for instance, in the left and right and/or fore and aft directions. The primary image data and the secondary image data may be distinct and/or may include portions that overlap with one another. Further, the primary image data and the secondary image data may be collected at the same or different resolutions. The collected primary image data and secondary image data are utilized to generate a single output image.

Abstract: Apparatuses and methods for enhancing a “primary” large format, digital, macro-image with “secondary” image data are provided. The secondary image data is collected utilizing one or more secondary optical systems having at least one electro-optical detector array (e.g., a CCD array) and a specific set of optical mirrors or optical prisms, arranged in such a way that the secondary optical systems extend the angular angle-of-view of the primary optical system and the resultant digital image in at least two opposing directions, for instance, in the left and right and/or fore and aft directions. The primary image data and the secondary image data may be distinct and/or may include portions that overlap with one another. Further, the primary image data and the secondary image data may be collected at the same or different resolutions. The collected primary image data and secondary image data are utilized to generate a single output image.

Abstract: Apparatuses and methods for enhancing a “primary” large format, digital, macro-image with “secondary” image data are provided. The secondary image data is collected utilizing one or more secondary optical systems having at least one electro-optical detector array (e.g., a CCD array) and a specific set of optical mirrors or optical prisms, arranged in such a way that the secondary optical systems extend the angular field-of-view of the primary optical system and the resultant digital image in at least two opposing directions, for instance, in the left and right and/or fore and aft directions. The primary image data and the secondary image data may be distinct and/or may include portions that overlap with one another. Further, the primary image data and the secondary image data may be collected at the same or different resolutions. The collected primary image data and secondary image data are utilized to generate a single output image.

Abstract: Large format, digital camera systems (10, 100, 150, 250, 310) expose single detector arrays 20 with multiple lens systems (12, 14, 16, 18) or multiple detector arrays (104, 106, 108, 110, 112, 114, 116, 118, 120, 152, 162, 172, 182, 252, 262, 272, 282, 322, 324) with one or more single lens systems (156, 166, 176, 186) to acquire sub-images of overlapping sub-areas of large area objects. The sub-images are stitched together to form a large format, digital, macro-image (80, 230?, 236?, 238?, 240?), which can be colored. Dampened camera carrier (400) and accelerometer (404) signals with double-rate digital signal processing (306, 308) are used.

Abstract: Large format, digital camera systems (10, 100, 150, 250, 310) expose single detector arrays 20 with multiple lens systems (12, 14, 16, 18) or multiple detector arrays (104, 106, 108, 110, 112, 114, 116, 118, 120, 152, 162, 172, 182, 252, 262, 272, 282, 322, 324) with one or more single lens systems (156, 166, 176, 186) to acquire sub-images of overlapping sub-areas of large area objects. The sub-images are stitched together to form a large format, digital, macro-image (80, 230?, 236?, 238?, 240?), which can be colored. Dampened camera carrier (400) and accelerometer (404) signals with double-rate digital signal processing (306, 308) are used.

Abstract: Large format, digital camera systems (10, 100, 150, 250, 310) expose single detector arrays 20 with multiple lens systems (12, 14, 16, 18) or multiple detector arrays (104, 106, 108, 110, 112, 114, 116, 118, 120, 152, 162, 172, 182, 252, 262, 272, 282, 322, 324) with one or more single lens systems (156, 166, 176, 186) to acquire sub-images of overlapping sub-areas of large area objects. The sub-images are stitched together to form a large format, digital, macro-image (80, 230?, 236?, 238?, 240?), which can be colored. Dampened camera carrier (400) and accelerometer (404) signals with double-rate digital signal processing (306, 308) are used.

Abstract: Large format, digital camera systems (10, 100, 150, 250, 310) expose single detector arrays 20 with multiple lens systems (12, 14, 16, 18) or multiple detector arrays (104, 106, 108, 110, 112, 114, 116, 118, 120, 152, 162, 172, 182, 252, 262, 272, 282, 322, 324) with one or more single lens systems (156, 166, 176, 186) to acquire sub-images of overlapping sub-areas of large area objects. The sub-images are stitched together to form a large format, digital, macro-image (80, 230″, 236″, 238″, 240″), which can be colored. Dampened camera carrier (400) and accelerometer (404) signals with double-rate digital signal processing (306, 308) are used.