11 citations · 20 across the 9 of their papers we have counts for
6 papers · 1 filter
MetaTele: Compact Refractive Metasurface Computational Telephoto Camera
Harshana Weligampola, Yuanrui Chen, Abhiram Gnanasambandam +4
Smartphone cameras face fundamental form-factor constraints that limit their optical magnification, primarily due to the difficulty of reducing a lens assembly's telephoto ratio, t…
GenMFSR: Generative Multi-Frame Image Restoration and Super-Resolution
Harshana Weligampola, Joshua Peter Ebenezer, Weidi Liu +4
Camera pipelines receive raw Bayer-format frames that need to be denoised, demosaiced, and often super-resolved. Multiple frames are captured to utilize natural hand tremors and en…
FlowSteer: Conditioning Flow Field for Consistent Image Restoration
Tharindu Wickremasinghe, Chenyang Qi, Harshana Weligampola +2
Flow-based text-to-image (T2I) models excel at prompt-driven image generation, but falter on Image Restoration (IR), often "drifting away" from being faithful to the measurement. P…
Diffusion Algorithm for Metalens Optical Aberration Correction
Harshana Weligampola, Yuanrui Chen, Weiheng Tang +2
Metalenses offer a path toward creating ultra-thin optical systems, but they inherently suffer from severe, spatially varying optical aberrations, especially chromatic aberration,…
Direct Kernel Optimization: Efficient Design for Opto-Electronic Convolutional Neural Networks
Ali Almuallem, Harshana Weligampola, Abhiram Gnanasambandam +5
Hybrid opto-electronic neural networks combine optical front-ends with electronic back-ends to perform vision tasks, but joint end-to-end (E2E) optimization of optical and electron…
A Retinex based GAN Pipeline to Utilize Paired and Unpaired Datasets for Enhancing Low Light Images
Harshana Weligampola, Gihan Jayatilaka, Suren Sritharan +4
Low light image enhancement is an important challenge for the development of robust computer vision algorithms. The machine learning approaches to this have been either unsupervise…