ReportDOI
Feature-Oriented Signal Processing Under Nonlinear Partial Differential Equations
Stanley Osher,Leonid I. Rudin +1 more
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In this article, a successful nonlinear partial differential equation based approach to restoration was carried out, ENO least squares, shock filters, feature detectors and total variation based deconvolution techniques were combined.Abstract:
: A successful nonlinear partial differential equation based approach to restoration was carried out, ENO least squares, shock filters, feature detectors and total variation based deconvolution techniques were combined. Also rigorous morphological methods and wavelet analysis were developed and used to restore noisy, blurry images.read more
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Book ChapterDOI
GANReDL: Medical Image Enhancement Using a Generative Adversarial Network with Real-Order Derivative Induced Loss Functions.
TL;DR: Deep (convolutional) neural networks (DCNN) have recently gained popularity, and shown improved performance in the field of image enhancement (de-noising and super-resolution, for instance), but the central issue of recovering finer texture details in images still remains unsolved.
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