Which outcome occurs when iterative deconvolution of microscope images fails?

💡 Explanation

Iterative deconvolution algorithms use inverse filtering; however, amplified noise from approximations becomes significant. This occurs because inverse filtering boosts frequencies equally regardless of signal strength, therefore noise dominates rather than revealing true features under stronger regularization.

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