Pixel-Dependent Blur Correction for Photogrammetric Image Capture
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Solution Overview
Problem
Existing image sharpening methods fail to adequately correct image blurring caused by complex movements of vehicles, such as pitching, yawing, or rolling, which are common in aircraft, leading to inadequate image sharpness for photogrammetric applications.
Innovation Solution
A pixel-dependent density function is used in a mathematical model to account for the varying influence of the camera's components on exposure across different pixels, allowing for improved image sharpness by modeling the relative motion between the camera and object during exposure.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If forward motion compensation is used to reduce image blur, then image sharpness is improved, but device complexity and cost increase
Solution Approach 1:
The patent replaces mechanical forward motion compensation systems with a computational approach. A processing unit uses a mathematical model incorporating pixel-dependent density functions to correct image blur after capture, eliminating the need for complex mechanical synchronization systems while achieving comparable or superior image sharpness
Solution Approach 2:
The patent changes the approach from mechanical parameter adjustment (physical sensor movement) to computational parameter processing. By using pixel-dependent density functions and mathematical deconvolution, the system processes image data parameters to correct blur, achieving image sharpness without mechanical complexity
2Manufacturing precision
If a stabilizing camera mount is used to compensate for vehicle movements, then image sharpness is improved to some extent, but device complexity and cost increase
Solution Approach 1:
The patent replaces mechanical stabilizing mounts with computational image processing. By using a mathematical model with pixel-dependent density functions to represent camera movements and applying deconvolution algorithms, the system achieves image sharpness correction without mechanical stabilization hardware
Solution Approach 2:
The patent introduces a processing unit and mathematical model as intermediaries between the captured blurred image and the final sharp image. The pixel-dependent density function acts as a mediator that characterizes the blur caused by camera movements, enabling computational correction without physical stabilization
3Manufacturing precision
If conventional image sharpening techniques are used, then some blur correction is achieved, but image sharpness remains inadequate for photogrammetric applications
Solution Approach 1:
The patent applies local quality by using pixel-dependent density functions that vary across different regions of the image. This allows the blur correction to be tailored to local characteristics, with each pixel or region having its own density function parameters, achieving superior sharpness and reliability for photogrammetric applications compared to uniform conventional sharpening
Solution Approach 2:
The patent performs preliminary action by first determining the pixel-dependent density function that characterizes the blur before applying deconvolution. This preparatory step of modeling the blur characteristics enables more accurate and reliable image sharpness correction suitable for photogrammetry
Data Source
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AI summary
In order to make high-quality captured images (1) possible in the event of a relative movement between an object (2) to be captured and a camera (3), a method for correcting image blurring is provided, wherein: a correlation between an image point (p) in the blurred captured image b(p) and an image point (p) of a sharpened captured image l(p) is modelled using a mathematical model; the model takes into account the relative movement between the camera and the object (2) during the exposure time and contains a density function which describes an influence of the camera (3) on the exposure during the exposure time; and in the mathematical model an image-point-dependent density function is used by means of which a different influence of the camera (3) on the exposure of different image points (p) of the captured image (1) is taken into account during the image correction.