Jitter Detection and Image Restoration for TDI CCD Satellite Images
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Solution Overview
Problem
Traditional methods for jitter detection and image restoration in high-resolution Time delay Integration Charge-Coupled device (TDI CCD) satellite images face challenges due to large calculation errors and inability to accurately account for transient satellite jitter, leading to image distortion and blur, especially with complex temporal changes.
Innovation Solution
A method based on a continuous dynamic shooting model (CDSM) that converts satellite jitter from image space to object space using an integral transformation function (ITF), employing a denser sampling strategy and adaptive image restoration combining time, space, and spectral information to reduce distortion and blur.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional discretization methods are used for push-broom imaging process, then calculation complexity is reduced, but jitter detection accuracy deteriorates due to large sampling intervals
Solution Approach 1:
The patent segments the continuous imaging process into discrete integration stages of the TDI CCD sensor. By dividing the exposure time into N integration stages and applying denser sampling at each stage, the method achieves accurate jitter detection without requiring overly complex continuous calculations throughout the entire imaging process
Solution Approach 2:
The patent introduces a continuous dynamic shooting model that dynamically adjusts the sampling strategy based on the actual imaging process. The model transitions from static traditional discretization to dynamic sampling that adapts to the temporal variations in satellite jitter, improving detection accuracy while maintaining computational feasibility
2Manufacturing precision
If the same point spread function is applied to the entire image for restoration, then processing simplicity is maintained, but restoration quality deteriorates due to inability to account for complex temporal jitter changes
Solution Approach 1:
The patent applies different point spread functions to different regions and time periods of the image. By estimating separate PSFs for each integration stage based on local jitter characteristics, the method achieves high restoration quality that accounts for temporal variations in satellite jitter, rather than using a single uniform PSF for the entire image
Solution Approach 2:
The patent performs preliminary jitter detection and PSF estimation before the actual image restoration process. By pre-calculating the point spread functions for each integration stage based on detected jitter parameters, the restoration process can directly apply appropriate PSFs without complex real-time calculations, balancing quality and computational efficiency
3Illumination intensity
If integration imaging techniques are used in TDI CCD, then luminous flux is increased and sensitivity is improved, but vulnerability to satellite jitter increases leading to image distortion and blur
Solution Approach 1:
The patent implements a feedback mechanism where jitter parameters are detected from the imaging data itself, and this detected jitter information is then used to guide the restoration process. By continuously monitoring and compensating for jitter effects through the detected parameters, the system maintains the benefits of integration imaging while correcting the harmful distortion and blur effects
Solution Approach 2:
The patent converts the harmful jitter-induced distortions into useful information for restoration. By detecting the jitter parameters from the actual imaging process and using them to estimate the point spread function, the method transforms the negative effect of jitter into a positive tool for achieving accurate image restoration that accounts for the actual satellite motion
Data Source
AI summary
A method of jitter detection and image restoration for high-resolution TDI CCD satellite images. The method includes: obtaining a parallax image after a sub-pixel matching method relying on a correlation coefficient and least squares algorithm; transferring a jitter offset from an image space to an object space by an integral transformation function (ITF); dealing with a continuous push-broom mode of cameras in a discrete way with a denser sampling strategy according to a continue dynamic shooting model (CDSM), obtaining a specialized CDSM and feeding it back to the ITF; applying the accurate ITF to the obtained parallax image and conducting the jitter curve fitting to achieve the jitter detection; estimating a correspondent partial PSF according to the CDSM and the obtained jitter curve; carrying out an adaptive restoration based on context through optimal window Wiener filtering, by means of multiple input and single output to completes the image restoration.