Search Results for author: Yash Sanghvi

Found 7 papers, 3 papers with code

Photon-Limited Deblurring using Algorithm Unrolling

no code implementations NeurIPS Workshop Deep_Invers 2021 Yash Sanghvi, Abhiram Gnanasambandam, Stanley Chan

Image deblurring in a photon-limited condition is ubiquitous in a variety of low-light applications such as photography, microscopy and astronomy.

Astronomy Deblurring +2

Photon Limited Non-Blind Deblurring Using Algorithm Unrolling

1 code implementation28 Oct 2021 Yash Sanghvi, Abhiram Gnanasambandam, Stanley H. Chan

Image deblurring in photon-limited conditions is ubiquitous in a variety of low-light applications such as photography, microscopy, and astronomy.

Astronomy Deblurring +2

Graph-Based Depth Denoising & Dequantization for Point Cloud Enhancement

no code implementations9 Nov 2021 Xue Zhang, Gene Cheung, Jiahao Pang, Yash Sanghvi, Abhiram Gnanasambandam, Stanley H. Chan

Specifically, we model depth formation as a combined process of signal-dependent noise addition and non-uniform log-based quantization.

Graph Learning Image Denoising +1

Photon-Limited Blind Deconvolution using Unsupervised Iterative Kernel Estimation

1 code implementation31 Jul 2022 Yash Sanghvi, Abhiram Gnanasambandam, Zhiyuan Mao, Stanley H. Chan

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.

Image Restoration

Structured Kernel Estimation for Photon-Limited Deconvolution

1 code implementation CVPR 2023 Yash Sanghvi, Zhiyuan Mao, Stanley H. Chan

By modeling the blur kernel using a low-dimensional representation with the key points on the motion trajectory, we significantly reduce the search space and improve the regularity of the kernel estimation problem.

Image Restoration

The Secrets of Non-Blind Poisson Deconvolution

no code implementations6 Sep 2023 Abhiram Gnanasambandam, Yash Sanghvi, Stanley H. Chan

Non-blind image deconvolution has been studied for several decades but most of the existing work focuses on blur instead of noise.

Image Deconvolution

Kernel Diffusion: An Alternate Approach to Blind Deconvolution

no code implementations4 Dec 2023 Yash Sanghvi, Yiheng Chi, Stanley H. Chan

Blind deconvolution problems are severely ill-posed because neither the underlying signal nor the forward operator are not known exactly.

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