Dongyu Du | Searcharxiv

arXiv2024

A Diffuse Light Field Imaging Model for Forward-Scattering Photon-Coded Signal Retrieval

Scattering imaging is often hindered by extremely low signal-to-noise ratios (SNRs) due to the prevalence of scattering noise. Light field imaging has been shown to be effective in suppressing noise and collect more ballistic photons as signals. However, to overcome the SNR limit in super-strong scattering environments, even with light field framework, only rare ballistic signals are insufficient. Inspired by radiative transfer theory, we propose a diffuse light field imaging model (DLIM) that leverages light field imaging to retrieve forward-scattered photons as signals to overcome the challenges of low-SNR imaging caused by super-strong scattering environments. This model aims to recover the ballistic photon signal as a source term from forward-scattered photons based on diffusion equations. The DLIM consists of two main processes: radiance modeling and diffusion light-field approximation. Radiate modeling analyzes the radiance distribution in scattering light field images using a proposed three-plane parameterization, which solves a 4-D radiate kernel describing the impulse function of scattering light field. Then, the scattering light field images synthesize a diffuse source satisfying the diffusion equation governing forward scattering photons, solved under Neumann boundary conditions in imaging space. This is the first physically-aware scattering light field imaging model, extending the conventional light field imaging framework from free space into diffuse space. The extensive experiments confirm that the DLIM can reconstruct the target objects even when scattering light field images are reduced as random noise at extremely low SNRs.

eess.IV↗

arXiv2024

DARTS: Diffusion Approximated Residual Time Sampling for Time-of-flight Rendering in Homogeneous Scattering Media

Time-of-flight (ToF) devices have greatly propelled the advancement of various multi-modal perception applications. However, achieving accurate rendering of time-resolved information remains a challenge, particularly in scenes involving complex geometries, diverse materials and participating media. Existing ToF rendering works have demonstrated notable results, yet they struggle with scenes involving scattering media and camera-warped settings. Other steady-state volumetric rendering methods exhibit significant bias or variance when directly applied to ToF rendering tasks. To address these challenges, we integrate transient diffusion theory into path construction and propose novel sampling methods for free-path distance and scattering direction, via resampled importance sampling and offline tabulation. An elliptical sampling method is further adapted to provide controllable vertex connection satisfying any required photon traversal time. In contrast to the existing temporal uniform sampling strategy, our method is the first to consider the contribution of transient radiance to importance-sample the full path, and thus enables improved temporal path construction under multiple scattering settings. The proposed method can be integrated into both path tracing and photon-based frameworks, delivering significant improvements in quality and efficiency with at least a 5x MSE reduction versus SOTA methods in equal rendering time.

cs.GR↗