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Related Experiment Video

Updated: May 21, 2026

Digital Inline Holographic Microscopy (DIHM) of Weakly-scattering Subjects

Digital Inline Holographic Microscopy (DIHM) of Weakly-scattering Subjects

Published on: February 8, 2014

Degradation-Adaptive Denoising: Aligning Diffusion Models With Physics of Video Snapshot Compressive Imaging.

Mingjin Zhang, Mingrui Li, Jie Guo

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society

|May 19, 2026

Summary

This study introduces PCD-Diffusion, a novel diffusion-based framework for Video Snapshot Compressive Imaging (SCI). It enhances reconstruction by aligning with the SCI physical model, improving motion detail and background smoothing.

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Last Updated: May 21, 2026

Digital Inline Holographic Microscopy (DIHM) of Weakly-scattering Subjects

Digital Inline Holographic Microscopy (DIHM) of Weakly-scattering Subjects

Published on: February 8, 2014

Area of Science:

Computational Imaging
Deep Learning for Imaging
Video Reconstruction

Background:

Video Snapshot Compressive Imaging (SCI) captures high-speed scenes efficiently.
Current SCI methods use feedforward networks with fixed denoising, limiting physical model alignment and balancing motion/static details.

Purpose of the Study:

To propose the first diffusion-based reconstruction framework, PCD-Diffusion, for Video SCI.
To address limitations in existing SCI methods regarding physical model alignment and reconstruction quality.

Main Methods:

Developed a Physically-Constrained Dynamic Diffusion (PCD-Diffusion) model for Video SCI.
Introduced a region-adaptive diffusion schedule and spatiotemporal residual estimation.
Incorporated motion prior-guided diffusion and Gauss-guided residual estimation for dynamic steering.

Main Results:

PCD-Diffusion explicitly aligns denoising with SCI's residual distribution.
The framework achieves superior reconstruction fidelity and temporal coherence.
Demonstrated effectiveness on both simulated and real-world datasets.

Conclusions:

PCD-Diffusion offers a significant advancement in Video SCI reconstruction.
The physically-constrained diffusion approach improves motion detail recovery and background smoothing.
The proposed method provides more accurate and temporally coherent reconstructions compared to existing techniques.