54 citations · 282 across the 74 of their papers we have counts for
76 papers
Anti-Aliasing Snapshot HDR Imaging Using Non-Regular Sensing
Teresa Stürzenhofäcker, Moritz Klimm, Jürgen Seiler +1
Snapshot HDR imaging is essential to capture the full dynamic range of a scene in a single exposure, making it essential for video and dynamic environments where motion prevents th…
Towards Object Segmentation Mask Selection Using Specular Reflections
Katja Kossira, Yunxuan Zhu, Jürgen Seiler +1
Specular reflections pose a significant challenge for object segmentation, as their sharp intensity transitions often mislead both conventional algorithms and deep learning based m…
Domain Adaptation for Camera-Specific Image Characteristics using Shallow Discriminators
Maximiliane Gruber, Jürgen Seiler, André Kaup
Each image acquisition setup leads to its own camera-specific image characteristics degrading the image quality. In learning-based perception algorithms, characteristics occurring…
Inter-Camera Color Correction for Multispectral Imaging with Camera Arrays Using a Consensus Image
Katja Kossira, Jürgen Seiler, André Kaup
This paper introduces a novel method for inter-camera color calibration for multispectral imaging with camera arrays using a consensus image. Capturing images using multispectral c…
Conditional Optimal Filter Selection for Multispectral Object Classification
Katja Kossira, David Schön, Jürgen Seiler +1
Capturing images using multispectral camera arrays has gained importance in medical, agricultural and environmental processes. However, using all available spectral bands is infeas…
Fast Edge-Aware Occlusion Detection in the Context of Multispectral Camera Arrays
Frank Sippel, Jürgen Seiler, André Kaup
Multispectral imaging is very beneficial in diverse applications, like healthcare and agriculture, since it can capture absorption bands of molecules in different spectral areas. A…
A Study on the Effect of Color Spaces in Learned Image Compression
Srivatsa Prativadibhayankaram, Mahadev Prasad Panda, Jürgen Seiler +4
In this work, we present a comparison between color spaces namely YUV, LAB, RGB and their effect on learned image compression. For this we use the structure and color based learned…
RGB-Guided Resolution Enhancement of IR Images
Marcel Trammer, Nils Genser, Jürgen Seiler
This paper introduces a novel method for RGB-Guided Resolution Enhancement of infrared (IR) images called Guided IR Resolution Enhancement (GIRRE). In the area of single image supe…
Conditional Residual Coding: A Remedy for Bottleneck Problems in Conditional Inter Frame Coding
Fabian Brand, Jürgen Seiler, André Kaup
Conditional coding is a new video coding paradigm enabled by neural-network-based compression. It can be shown that conditional coding is in theory better than the traditional resi…
Cross Spectral Image Reconstruction Using a Deep Guided Neural Network
Frank Sippel, Jürgen Seiler, André Kaup
Cross spectral camera arrays, where each camera records different spectral content, are becoming increasingly popular for RGB, multispectral and hyperspectral imaging, since they a…
End-to-End Lidar-Camera Self-Calibration for Autonomous Vehicles
Arya Rachman, Jürgen Seiler, André Kaup
Autonomous vehicles are equipped with a multi-modal sensor setup to enable the car to drive safely. The initial calibration of such perception sensors is a highly matured topic and…
Analysis of mesh-based motion compensation in wavelet lifting of dynamical 3-D+t CT data
Wolfgang Schnurrer, Thomas Richter, Jürgen Seiler +1
Factorized in the lifting structure, the wavelet transform can easily be extended by arbitrary compensation methods. Thereby, the transform can be adapted to displacements in the s…
Compression of Dynamic Medical CT Data Using Motion Compensated Wavelet Lifting with Denoised Update
Daniela Lanz, Jürgen Seiler, Karina Jaskolka +1
For the lossless compression of dynamic 3-D+t volumes as produced by medical devices like Computed Tomography, various coding schemes can be applied. This paper shows that 3-D subb…
Centroid adapted frequency selective extrapolation for reconstruction of lost image areas
Wolfgang Schnurrer, Markus Jonscher, Jürgen Seiler +3
Lost image areas with different size and arbitrary shape can occur in many scenarios such as error-prone communication, depth-based image rendering or motion compensated wavelet li…
Analysis of displacement compensation methods for wavelet lifting of medical 3-D thorax CT volume data
Wolfgang Schnurrer, Jürgen Seiler, Eugen Wige +1
A huge advantage of the wavelet transform in image and video compression is its scalability. Wavelet-based coding of medical computed tomography (CT) data becomes more and more pop…
Efficient lossless coding of highpass bands from block-based motion compensated wavelet lifting using JPEG 2000
Wolfgang Schnurrer, Tobias Tröger, Thomas Richter +2
Lossless image coding is a crucial task especially in the medical area, e.g., for volumes from Computed Tomography or Magnetic Resonance Tomography. Besides lossless coding, compen…
On the influence of clipping in lossless predictive and wavelet coding of noisy images
Wolfgang Schnurrer, Jürgen Seiler, Michael Schöberl +1
Especially in lossless image coding the obtainable compression ratio strongly depends on the amount of noise included in the data as all noise has to be coded, too. Different appro…
Improving block-based compensated wavelet lifting by reconstructing unconnected pixels
Wolfgang Schnurrer, Jürgen Seiler, André Kaup
This paper presents a new approach for improving the visual quality of the lowpass band of a compensated wavelet transform. A high quality of the lowpass band is very important as…
3-D mesh compensated wavelet lifting for 3-D+t medical CT data
Wolfgang Schnurrer, Thomas Richter, Jürgen Seiler +2
For scalable coding, a high quality of the lowpass band of a wavelet transform is crucial when it is used as a downscaled version of the original signal. However, blur and motion c…
Temporal error concealment for fisheye video sequences based on equisolid re-projection
Andrea Eichenseer, Jürgen Seiler, Michel Bätz +1
Wide-angle video sequences obtained by fisheye cameras exhibit characteristics that may not very well comply with standard image and video processing techniques such as error conce…
Domain Adaptation for Unknown Image Distortions in Instance Segmentation
Maximiliane Gruber, Fabian Brand, Alina Mosebach +2
Data-driven techniques for machine vision heavily depend on the training data to sufficiently resemble the data occurring during test and application. However, in practice unknown…
On Benefits and Challenges of Conditional Interframe Video Coding in Light of Information Theory
Fabian Brand, Jürgen Seiler, André Kaup
The rise of variational autoencoders for image and video compression has opened the door to many elaborate coding techniques. One example here is the possibility of conditional int…
Synthesizing Annotated Image and Video Data Using a Rendering-Based Pipeline for Improved License Plate Recognition
Andreas Spruck, Maximilane Gruber, Anatol Maier +4
An insufficient number of training samples is a common problem in neural network applications. While data augmentation methods require at least a minimum number of samples, we prop…
3D Rendering Framework for Data Augmentation in Optical Character Recognition
Andreas Spruck, Maximiliane Hawesch, Anatol Maier +3
In this paper, we propose a data augmentation framework for Optical Character Recognition (OCR). The proposed framework is able to synthesize new viewing angles and illumination sc…