Deconvolution is a mathematical technique used to reverse the effects of convolution on signals, allowing for the recovery of original information that has been distorted by a process such as noise or blurring. It plays a vital role in various applications, particularly in image processing, where it helps in reconstructing clearer images from blurred ones, and in signal processing, where it improves the quality of signals affected by noise. Understanding deconvolution is crucial for implementing effective regularization strategies in non-linear problems and enhancing image denoising and deblurring processes.
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