Digital image processing is a subfield of digital signal processing that deals with the processing and manipulation of digital images. It involves the use of algorithms and techniques to perform various operations on images, such as image enhancement, image restoration, image segmentation, and image compression.
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Restoration aims to recover a degraded image. Sridhar introduces noise models (Gaussian, salt-and-pepper, Rayleigh) and restoration filters (Inverse, Wiener, and Kalman filters). He carefully explains the difference between enhancement (subjective) and restoration (objective, based on degradation models). The inclusion of the Lucy-Richardson algorithm for deblurring adds depth for advanced readers.