Year: 2024
Type: conference-paper
Abstract: pipeline still faces challenges including the lack of joint optimization in system components, computational redundancies, and optical distortions such as lens shading.In light of this, we propose an end-to-end camera imaging pipeline (RealCamNet) to enhance realworld camera imaging performance.Our methodology diverges from conventional, fragmented multi-stage image signal processing towards end-to-end architecture.This architecture facilitates joint optimization across the full pipeline and the restoration of coordinate-biased distortions.RealCamNet is designed for highquality conversion from RAW to RGB and compact image compression.Specifically, we deeply analyze coordinate-dependent optical distortions, e.g., vignetting and dark shading, and design a novel 2804
Authors: Kepeng Xu, Zijia Ma, Li Xu, Gang He, Yunsong Li, Wenxin Yu, Taichu Han, Cheng Yang
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: bronze
Award: G7777819896
OpenAlex ID: W4403791438