750 citations · 1.4k across the 30 of their papers we have counts for
10 papers · 1 filter
Blindly Deconvolving Super-noisy Blurry Image Sequences
Leonid Kostrykin, Stefan Harmeling
Image blur and image noise are imaging artifacts intrinsically arising in image acquisition. In this paper, we consider multi-frame blind deconvolution (MFBD), where image blur is…
Deblurring Photographs of Characters Using Deep Neural Networks
Thomas Germer, Tobias Uelwer, Stefan Harmeling
In this paper, we present our approach for the Helsinki Deblur Challenge (HDC2021). The task of this challenge is to deblur images of characters without knowing the point spread fu…
Contour Proposal Networks for Biomedical Instance Segmentation
Eric Upschulte, Stefan Harmeling, Katrin Amunts +1
We present a conceptually simple framework for object instance segmentation called Contour Proposal Network (CPN), which detects possibly overlapping objects in an image while simu…
Fast Multi-Level Foreground Estimation
Thomas Germer, Tobias Uelwer, Stefan Conrad +1
Alpha matting aims to estimate the translucency of an object in a given image. The resulting alpha matte describes pixel-wise to what amount foreground and background colors contri…
PyMatting: A Python Library for Alpha Matting
Thomas Germer, Tobias Uelwer, Stefan Conrad +1
An important step of many image editing tasks is to extract specific objects from an image in order to place them in a scene of a movie or compose them onto another background. Alp…
Improving Cytoarchitectonic Segmentation of Human Brain Areas with Self-supervised Siamese Networks
Hannah Spitzer, Kai Kiwitz, Katrin Amunts +2
Cytoarchitectonic parcellations of the human brain serve as anatomical references in multimodal atlas frameworks. They are based on analysis of cell-body stained histological secti…
Parcellation of Visual Cortex on high-resolution histological Brain Sections using Convolutional Neural Networks
Hannah Spitzer, Katrin Amunts, Stefan Harmeling +1
Microscopic analysis of histological sections is considered the "gold standard" to verify structural parcellations in the human brain. Its high resolution allows the study of lamin…
Learning to Deblur
Christian J. Schuler, Michael Hirsch, Stefan Harmeling +1
We describe a learning-based approach to blind image deconvolution. It uses a deep layered architecture, parts of which are borrowed from recent work on neural network learning, an…
Image denoising with multi-layer perceptrons, part 1: comparison with existing algorithms and with bounds
Harold Christopher Burger, Christian J. Schuler, Stefan Harmeling
Image denoising can be described as the problem of mapping from a noisy image to a noise-free image. The best currently available denoising methods approximate this mapping with cl…
Image denoising with multi-layer perceptrons, part 2: training trade-offs and analysis of their mechanisms
Harold Christopher Burger, Christian J. Schuler, Stefan Harmeling
Image denoising can be described as the problem of mapping from a noisy image to a noise-free image. In another paper, we show that multi-layer perceptrons can achieve outstanding…