The Lucy-Richardson Algorithm for Image Restoration
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Resource Overview
The Lucy-Richardson algorithm effectively restores blurred and noisy images when the point-spread function PSF (blurring operator) is known, but noise information is limited or unavailable. This iterative, accelerated, damped algorithm improves image quality while preserving critical features, with implementation typically involving deconvolution functions and PSF parameter optimization.
Detailed Documentation
In numerous scenarios, we require algorithms to process images corrupted by blur and noise. The Lucy-Richardson algorithm serves as a widely-used image restoration technique. It proves particularly effective when the point-spread function PSF (blurring operator) is known, but noise information remains scarce or absent. To enhance restoration quality, additional optical system characteristics (such as camera parameters) can be incorporated as input parameters. Through iterative, accelerated, and damped Lucy-Richardson deconvolution, we can restore blurred and noisy images while preserving crucial image features. Implementation typically involves specifying the PSF matrix, setting iteration counts, and applying regularization techniques to control noise amplification during restoration.
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