74 citations · 200 across the 35 of their papers we have counts for
7 papers · 1 filter
Zero-shot Denoising via Neural Compression: Theoretical and algorithmic framework
Ali Zafari, Xi Chen, Shirin Jalali
Zero-shot denoising aims to denoise observations without access to training samples or clean reference images. This setting is particularly relevant in practical imaging scenarios…
Multilook Coherent Imaging: Theoretical Guarantees and Algorithms
Xi Chen, Soham Jana, Christopher A. Metzler +2
Multilook coherent imaging is a widely used technique in applications such as digital holography, ultrasound imaging, and synthetic aperture radar. A central challenge in these sys…
DeCompress: Denoising via Neural Compression
Ali Zafari, Xi Chen, Shirin Jalali
Learning-based denoising algorithms achieve state-of-the-art performance across various denoising tasks. However, training such models relies on access to large training datasets c…
Bayesian Despeckling of Structured Sources
Ali Zafari, Shirin Jalali
Speckle noise is a fundamental challenge in coherent imaging systems, significantly degrading image quality. Over the past decades, numerous despeckling algorithms have been develo…
Theoretical Characterization of Effect of Masks in Snapshot Compressive Imaging
Mengyu Zhao, Shirin Jalali
Snapshot compressive imaging (SCI) refers to the recovery of three-dimensional data cubes-such as videos or hyperspectral images-from their two-dimensional projections, which are g…
Comprehensive Examination of Unrolled Networks for Solving Linear Inverse Problems
Eric Chen, Xi Chen, Arian Maleki +1
Unrolled networks have become prevalent in various computer vision and imaging tasks. Although they have demonstrated remarkable efficacy in solving specific computer vision and co…