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Found 10 papers, 2 papers with code
Photon-Limited Blind Deconvolution using Unsupervised Iterative Kernel Estimation
When the noise is strong, these networks fail to simultaneously deblur and denoise; (3) While iterative schemes are known to be robust in the classical frameworks, they are seldom considered in deep neural networks because it requires a differentiable non-blind solver.
Exposure-Referred Signal-to-Noise Ratio for Digital Image Sensors
New theoretical results are derived for image sensors of any bit-depth and full-well capacity.
Graph-Based Depth Denoising & Dequantization for Point Cloud Enhancement
Specifically, we model depth formation as a combined process of signal-dependent noise addition and non-uniform log-based quantization.
Photon Limited Non-Blind Deblurring Using Algorithm Unrolling
Image deblurring in photon-limited conditions is ubiquitous in a variety of low-light applications such as photography, microscopy, and astronomy.
Photon-Limited Deblurring using Algorithm Unrolling
Image deblurring in a photon-limited condition is ubiquitous in a variety of low-light applications such as photography, microscopy and astronomy.
HDR Imaging with Quanta Image Sensors: Theoretical Limits and Optimal Reconstruction
We provide a complete theoretical characterization of the sensor in the context of HDR imaging, by proving the fundamental limits in the dynamic range that QIS can offer and the trade-offs with noise and speed.
Dynamic Low-light Imaging with Quanta Image Sensors
QIS are single-photon image sensors with photon counting capabilities.
Image Classification in the Dark using Quanta Image Sensors
In this paper, we present a new low-light image classification solution using Quanta Image Sensors (QIS).
Megapixel Photon-Counting Color Imaging using Quanta Image Sensor
Quanta Image Sensor (QIS) is a single-photon detector designed for extremely low light imaging conditions.
