Diagonal Camera Sensors for Oblique Imagery Distortion Correction
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Solution Overview
Problem
Current photogrammetry techniques face limitations in performance, efficiency, and utility, particularly in capturing oblique imagery, as they often require complex lens designs and result in inefficient use of resources, such as film or pixels, and do not effectively capture relative heights and vertical surfaces.
Innovation Solution
The use of a camera-set with oblique cameras positioned at diagonal angles and distortion correcting electronic image sensors, which align their projected rows or columns with the direction of flight, allowing for wider swaths and improved coverage without the need for complex lens designs, and enabling the capture of oblique imagery from cardinal or intercardinal directions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If complex lens designs are used to capture oblique imagery, then image quality may be improved, but device complexity and manufacturing costs increase
Solution Approach 1:
The patent replaces complex optical lens designs with a computational approach using distortion correcting sensors and image processing algorithms. The sensor captures raw distorted imagery, and software algorithms correct the distortion to produce high-quality oblique images, eliminating the need for complex mechanical lens systems.
Solution Approach 2:
The patent changes the parameter of sensor orientation from standard orthogonal alignment to diagonal alignment relative to the flight direction. This parameter change, combined with computational correction, achieves high image quality while using simpler lens designs optimized for the diagonal configuration.
2Ease of manufacture
If standard orthogonal camera alignment is used, then manufacturing is simpler, but swath width and coverage efficiency are reduced
Solution Approach 1:
The patent introduces asymmetry by aligning the camera sensor diagonally at a 45-degree angle relative to the flight direction rather than using standard orthogonal alignment. This asymmetric configuration increases the effective swath width and improves coverage efficiency while maintaining manageable manufacturing complexity through standardized sensor mounting procedures.
3Productivity
If diagonal sensor alignment is implemented, then swath width and coverage are improved, but image distortion increases
Solution Approach 1:
The patent replaces mechanical precision requirements with computational correction. Instead of requiring precise optical components to minimize distortion, the system uses software algorithms that automatically correct distortion based on the known diagonal sensor geometry, achieving high precision results with simpler hardware.
Solution Approach 2:
The patent applies preliminary geometric correction during the image processing stage by applying transformation algorithms that pre-correct for the expected distortion patterns based on diagonal sensor alignment, eliminating the need for complex real-time distortion compensation.
4Reliability
If multiple orthogonal cameras are used to capture all directions, then complete coverage is achieved, but resource usage and costs increase
Solution Approach 1:
The patent makes a single diagonal camera configuration perform the function of multiple orthogonal cameras by capturing imagery that, when processed with appropriate geometric corrections, provides equivalent coverage and information content, thereby reducing resource consumption while maintaining coverage completeness.
Data Source
AI summary
A vehicle collects oblique imagery along a nominal heading using rotated camera-groups with optional distortion correcting electronic image sensors that align projected pixel columns or rows with a pre-determined direction on the ground, thereby improving collection quality, efficiency, and/or cost. In a first aspect, the camera-groups are rotated diagonal to the nominal heading. In a second aspect, the distortion correcting electronic image sensors align projected pixel columns or rows with a pre determined direction on the ground. In a third aspect, the distortion correcting electronic image sensors are rotated around the optical axis of the camera. In a fourth aspect, cameras collect images in strips and the strips from different cameras overlap, providing large-baseline, small-time difference stereopsis.