Forward-and-backward diffusion processes for adaptive image enhancement and denoising

By Guy Gilboa, Nir A. Sochen, Yehoshua Y. Zeevi. IEEE Transactions on Image Processing, 2002

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Histology image analysis for carcinoma detection and grading (2012, methodology): “Traditional enhancement techniques include adaptive filters [53] and inverse anisotropic diffusions [49].”
Trainable Nonlinear Reaction Diffusion: A Flexible Framework for Fast and Effective Image Restoration (2015, background): “vious work [23], which leads to an adaptive forward-and-”
Super-resolution: a comprehensive survey (2014, neutral): “the concept of POCS [7] (1989), [38], [42], [43], [49], [53], [72], [77], [93], [103], [122], [155], [175], [184], [204], [243], [351].”
Image up-sampling using total-variation regularization with a new observation model (2005, neutral): “In [43]–[47], was only designed on by assuming that the filter shown in Fig.”
On learning optimized reaction diffusion processes for effective image restoration (2015, positive): “We find that the learned influence function (b) is closely similar to an elaborately designed function in a previous work [17], which leads to an adaptive forwardand-backward diffusion process.”