CircleFlow: Flow-Guided Camera Blur Estimation using a Circle Grid Target

TL;DR

CircleFlow is a novel framework for high-precision camera blur estimation that uses a structured circle grid target and flow-guided edge localization to accurately model spatially varying PSFs, improving optical calibration and computational vision tasks.

Contribution

It introduces a flow-guided edge localization method combined with a structured capture and neural PSF modeling, advancing the accuracy and robustness of PSF estimation.

Findings

Achieves state-of-the-art accuracy in PSF estimation.

Demonstrates robustness on both simulated and real-world data.

Provides a practical framework for camera calibration and deblurring.

Abstract

The point spread function (PSF) serves as a fundamental descriptor linking the real-world scene to the captured signal, manifesting as camera blur. Accurate PSF estimation is crucial for both optical characterization and computational vision, yet remains challenging due to the inherent ambiguity and the ill-posed nature of intensity-based deconvolution. We introduce CircleFlow, a high-fidelity PSF estimation framework that employs flow-guided edge localization for precise blur characterization. CircleFlow begins with a structured capture that encodes locally anisotropic and spatially varying PSFs by imaging a circle grid target, while leveraging the target's binary luminance prior to decouple image and kernel estimation. The latent sharp image is then reconstructed through subpixel alignment of an initialized binary structure guided by optical flow, whereas the PSF is modeled as an energy-constrained implicit neural representation. Both components are jointly optimized within a demosaicing-aware differentiable framework, ensuring physically consistent and robust PSF estimation enabled by accurate edge localization. Extensive experiments on simulated and real-world data demonstrate that CircleFlow achieves state-of-the-art accuracy and reliability, validating its effectiveness for practical PSF calibration.