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ACM MM2024Top-tier venue

An End-to-End Real-World Camera Imaging Pipeline

Kepeng Xu, Zijia Ma, Li Xu, Gang He, Yunsong Li, Wenxin Yu, Taichu Han, Cheng Yang

2024Year
9Citations
2Top-tier citations

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

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