Nov 11, 2013 · SUMMARY. Considering the real existent fact of the ideal edge and the learning style of image analogy without reference parameters, ...
We show that a specific local image patch with degradation characteristic can be utilized for restoring the whole image. In the training process, a clear ...
Nov 1, 2013 · We show that a specific local image patch with degradation characteristic can be utilized for restoring the whole image. In the training process ...
Dec 27, 2021 · In this paper, we propose the image Edge Restoring Filter (ERF) to restore the blur edge pixels in the output of local smoothing filters to be clear.
Missing: Ideal | Show results with:Ideal
Learning from Ideal Edge for Image Restoration. By: Ni, Guo-Qiang · He, Jin-Ping · Gao, Kun. Material type: ArticleDescription: 2487-2491 pSubject(s):.
Therefore, enhancing low-light images requires comprehensive recon- struction techniques such as contrast enhancement, noise reduction, and detail restoration.
If the goal is for the network to learn to produce visually pleasing images, it stands to reason that the error function should be perceptually motivated, as is ...
Mar 11, 2024 · We present a lightweight plugin, pre-training guided refining module (PTG-RM), to leverage pre-trained models for enhancing image restoration.
Feb 25, 2024 · With deep learning, image reconstruction restores and creates high-quality images from incomplete, noisy, or low-resolution input data.
MRI restoration using edge-guided adversarial learning - PMC - NCBI
www.ncbi.nlm.nih.gov › PMC7977797
May 13, 2020 · Our proposed method consists of two steps: edge connection and contrast completion; both steps follow an adversarial model, consisting a ...