Optical analog computing under partially coherent illumination offers a promising route toward high-speed, low-noise, and interference-robust information processing. However, the role of spatial coherence in optical differentiation has not been fully explored. Here, we demonstrate spatial differential imaging under Gaussian–Schell model illumination and show that the output intensity comprises three distinct contributions: object differentiation, mode differentiation, and cross terms. This decomposition reveals a fundamental coherence-driven trade-off: while reduced coherence suppresses speckle noise to improve edge smoothness, mode differentiation and cross terms introduce an object-dependent structured background that degrades contrast. By quantifying this interplay through theory and experiment, we identify an optimal coherence window (0.6 < μ < 1) that balances edge smoothness and contrast. These results establish a practical guideline for spatial optical differentiation under partially coherent light, advancing robust optical analog computing and imaging applications.
Compared with conventional intensity imaging, complex optical field imaging enables the recovery of both amplitude and phase information of the optical field, and has become an important tool in label-free microscopy, surface metrology, and crystal characterization. However, because conventional detectors can only meas...
Shi-Xin Hu, Xian-Ye Li, Yi-Kang He et al.· Light Manipulation and Appli...· 0 citations
Delay-and-sum (DAS) beamforming is widely used in ultrasound flow imaging due to its computational simplicity; however, its high sidelobe levels significantly degrade image contrast. Coherence factor (CF) beamforming partially alleviates this limitation by emphasizing spatial coherence, yet residual incoherent energy r...
Nizar Guezzi, Sangheon Lee, Sangwoo Nam et al.· Ultrasonics· 0 citations
This work proposes an adaptive modulation strategy driven by the initial input that synthesizes effective nonlinearity within a standard linear optical framework, and reveals that shallow nonlinear architectures can outperform significantly deeper linear counterparts, demonstrating that computational nonlinearity can e...
Yu-Chuan Shao, Hai-Qi Gao, Zi-Yan Zhang et al.· Laser & Photonics Review...· 0 citations
It is shown that, for classification tasks, a well-designed optical frontend reshapes the statistics of the sensor intensity readout to improve class separability, quantified by the Bhattacharyya distance.
Nicholas Behrens, Yan-Dong Li, F. Monticone· 0 citations
Field-dependent blur and frequency-response loss limit miniature confocal endoscopic imaging. We introduce a physics-prior-guided dual-branch residual network that combines the degraded image with normalized field coordinates and calibration-derived MTF, PSF, SNR, and intensity-response maps. For the representative per...
Zhi Wang, Xue-Yi Wang, Yi-Ning Mu et al.· Optics Express· 0 citations
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