58 citations · 112 across the 10 of their papers we have counts for
10 papers
Multiple-level Green Noise Mask Design for Practical Fourier Phase Retrieval
Qiuliang Ye, Bingo Wing-Kuen Ling, Li-Wen Wang +1
Phase retrieval, a long-established challenge for recovering a complex-valued signal from its Fourier intensity measurements, has attracted significant interest because of its far-…
Towards Practical Single-shot Phase Retrieval with Physics-Driven Deep Neural Network
Qiuliang Ye, Li-Wen Wang, Daniel Pak-Kong Lun
Phase retrieval (PR), a long-established challenge for recovering a complex-valued signal from its Fourier intensity-only measurements, has attracted considerable attention due to…
Improved Multiple-Image-Based Reflection Removal Algorithm Using Deep Neural Networks
Tingtian Li, Yuk-Hee Chan, Daniel P. K. Lun
When imaging through a semi-reflective medium such as glass, the reflection of another scene can often be found in the captured images. It degrades the quality of the images and af…
SiSPRNet: End-to-End Learning for Single-Shot Phase Retrieval
Qiuliang Ye, Li-Wen Wang, Daniel P. K. Lun
With the success of deep learning methods in many image processing tasks, deep learning approaches have also been introduced to the phase retrieval problem recently. These approach…
Robust Phase Retrieval with Green Noise Binary Masks
Qiuliang Ye, Yuk-Hee Chan, Michael G. Somekh +1
Phase retrieval with pre-defined optical masks can provide extra constraint and thus achieve improved performance. The recent progress in optimization theory demonstrates the super…
Enhancing and Learning Denoiser without Clean Reference
Rui Zhao, Daniel P. K. Lun, Kin-Man Lam
Recent studies on learning-based image denoising have achieved promising performance on various noise reduction tasks. Most of these deep denoisers are trained either under the sup…