Výsledky vyhľadávania - "JPEG artifact removal"

Boosting the Performance of Image Restoration Models Through Training With Deep-Feature Auxiliary Guidance

Autori: Cheolhun Jang Daehyun Ji Nam Ik Cho

Zdroj: IEEE Access, Vol 13, Pp 173398-173414 (2025)

Predmety: JPEG artifact removal, image deblurring, image denoising, image restoration, super-resolution, Electrical engineering. Electronics. Nuclear engineering, TK1-9971

Popis súboru: electronic resource

Relation: https://ieeexplore.ieee.org/document/11192423/; https://doaj.org/toc/2169-3536

Prístupová URL adresa: https://doaj.org/article/053e8f568a0645ac9c29c47169592c9c

Efficient and Effective Blind JPEG Image Improvement With Sequential Feature Processing

Autori: Shinya Ezumi Masaaki Ikehara

Zdroj: IEEE Access, Vol 12, Pp 151975-151986 (2024)

Predmety: double compressed image, JPEG, Deep learning, JPEG artifact removal, Electrical engineering. Electronics. Nuclear engineering, JPEG image improvement, image processing, TK1-9971

Prístupová URL adresa: https://doaj.org/article/da74db65cad549dd91babe90184881a2

Enhancing performance of conventional image codecs using CNN based image sub-sampling and super resolution

Autori: Saha, Susmita Yahampath, Pradeepa University of Manitoba

Prispievatelia: Saha, Susmita Yahampath, Pradeepa University of Manitoba

Predmety: Image pre-processing, Image super resolution, Image compression, Deep learning, JPEG artifact removal, Image post-processing, CNN

Popis súboru: application/pdf

Prístupová URL adresa: https://hdl.handle.net/1993/35142

Enhancing performance of conventional image codecs using CNN based image sub-sampling and super resolution

Autori: McLeod, Robert (Electrical and Computer Engineering) Pawlak, Miroslaw (Electrical and Computer Engineering) Yahampath, Pradeepa (Electrical and Computer Engineering) Saha, Susmita

Témy: Image compression, Image pre-processing, Image post-processing, Deep learning, CNN, JPEG artifact removal, Image super resolution, master thesis

URL: http://hdl.handle.net/1993/35142