arXiv subjects

Ni Chen

Publications and source records attributed to Ni Chen.

6 recordsLinked to original sources

arXiv2026

Rapid tracking through strongly scattering media with physics-informed neuromorphic speckle analysis

This work addresses the critical problem of tracking fast-moving objects through strongly scattering media in a low-light environment. Different from existing approaches that use frame-based cameras with fixed exposure times, which trade off signal-to-noise ratio for temporal resolution, we introduce computational neuromorphic tracking (CNT), a physics-informed framework that combines asynchronous event sensing with task-driven speckle analysis for robust motion estimation. We formulate the neuromorphic speckle aggregation as a spatiotemporal speckle representation, jointly optimizing the temporal and spatial parameters to maximize tracking stability under extreme conditions. Extensive experiments demonstrate that our method enables robust motion tracking of 10x faster motion and under 10x dimmer illumination compared to conventional systems. These improvements significantly broaden the operational regime for tracking through scattering media, providing an efficient and scalable solution for demanding scenarios involving rapid motion and low-light conditions.

cs.CV↗

arXiv2024

Align-Free Multi-Plane Phase Retrieval

The multi-plane phase retrieval method provides a budget-friendly and effective way to perform phase imaging, yet it often encounters alignment challenges due to shifts along the optical axis in experiments. Traditional methods, such as employing beamsplitters instead of mechanical stage movements or adjusting focus using tunable light sources, add complexity to the setup required for multi-plane phase retrieval. Attempts to address these issues computationally face difficulties due to the variable impact of diffraction, which renders conventional homography techniques inadequate. In our research, we introduce a novel Adaptive Cascade Calibrated (ACC) strategy for multi-plane phase retrieval that overcomes misalignment issues. This technique detects feature points within the refocused sample space and calculates the transformation matrix for neighboring planes on-the-fly to digitally adjust measurements, facilitating alignment-free multi-plane phase retrieval. This approach not only avoids the need for complex and expensive optical hardware but also simplifies the imaging setup, reducing overall costs. The effectiveness of our method is validated through simulations and real-world optical experiments.

physics.optics↗

arXiv2018

Analysis of Fourier ptychographic microscopy with half of the captured images

Fourier ptychography microscopy (FPM) is a new computational imaging technique that can provide gigapixel images with both high resolution and a wide field of view (FOV). However, time consuming of the data-acquisition process is a critical issue. In this paper, we make an analysis on the FPM imaging system with half number of the captured images. Based on the image analysis of the conventional FPM system, we then compare the reconstructed images with different number of captured data. Simulation and experiment results show that the reconstructed image with half number captured data do not show obvious resolution degradation compared to that with all the captured data, except a contrast reduction. In particular in the case when the object is close to phase-only/amplitude only, the quality of the reconstructed image with half of the captured data is nearly as good as the one reconstructed with full data.

eess.IV↗

arXiv2018

Fast and robust misalignment correction of Fourier ptychographic microscopy

Fourier ptychographi cmicroscopy(FPM) is a newly developed computational imaging technique that can provide gigapixel images with both high resolution (HR) and wide field of view (FOV). However, the positional misalignment of the LED array induces a degradation of the reconstruction, especially in the regions away from the optical axis. In this paper, we propose a robust and fast method to correct the LED misalignment of FPM, termed as misalignment correction for FPM (mcFPM). Although different regions in the FOV have different sensitivity to the LED misalignment, the experimental results show that mcFPM is robust to eliminate the degradation in each region. Compared with the state-of-the-art methods, mcFPM is much faster.

cs.CV↗

arXiv2017

Fast and High Quality Light Field Acquisition using Defocus Modulation

Light field reconstruction from images captured by focal plane sweeping, such as light field moment imaging (LFMI) and light field reconstruction with back projection (LFBP), can achieve high lateral resolution comparable to the modern camera sensor. This is impossible for the conventional lens array based light field capture systems. However, capturing a series of focal sweeping images along the optical axis is time consuming and requires fine alignment, and different focal plane based light field reconstruction techniques require images with different characteristics. To solve this problem, we present an efficient approach for fast light field acquisition with precise focal plane sweeping capture by defocus modulation rather than axial movement. Because of the controllable point spread function, we can capture images for light field reconstruction with both LFMI and LFBP.

physics.optics↗

arXiv2016

Analysis of the noise in back-projection light field acquisition and its optimization

Light field reconstruction from images captured by focal plane sweeping can achieve high lateral resolution comparable to the modern camera sensor. This is impossible for the conventional micro-lenslet based light field capture systems. However, the severe defocus noise and the low depth resolution limit its applications. In this paper, we analyze the defocus noise and the depth resolution in the focal plane sweeping based light field reconstruction technique, and propose a method to reduce the defocus noise and improve the depth resolution. Both numerical and experimental results verify the proposed method.

cs.CV↗