58 citations · 563 across the 59 of their papers we have counts for
33 papers · 1 filter
Learning-Based Conditional Image Coder Using Color Separation
Panqi Jia, Ahmet Burakhan Koyuncu, Georgii Gaikov +3
Recently, image compression codecs based on Neural Networks(NN) outperformed the state-of-art classic ones such as BPG, an image format based on HEVC intra. However, the typical NN…
Device Interoperability for Learned Image Compression with Weights and Activations Quantization
Esin Koyuncu, Timofey Solovyev, Elena Alshina +1
Learning-based image compression has improved to a level where it can outperform traditional image codecs such as HEVC and VVC in terms of coding performance. In addition to good c…
Optimization of Probability Distributions for Residual Coding of Screen Content
Hannah Och, Tilo Strutz, André Kaup
Probability distribution modeling is the basis for most competitive methods for lossless coding of screen content. One such state-of-the-art method is known as soft context formati…
A Bit Stream Feature-Based Energy Estimator for HEVC Software Encoding
Geetha Ramasubbu, André Kaup, Christian Herglotz
The total energy consumption of today's video coding systems is globally significant and emphasizes the need for sustainable video coder applications. To develop such sustainable v…
Frame Rate Up-Conversion Using Key Point Agnostic Frequency-Selective Mesh-to-Grid Resampling
Viktoria Heimann, Andreas Spruck, André Kaup
High frame rates are desired in many fields of application. As in many cases the frame repetition rate of an already captured video has to be increased, frame rate up-conversion (F…
Modeling of Energy Consumption and Streaming Video QoE using a Crowdsourcing Dataset
Christian Herglotz, Werner Robitza, Matthias Kränzler +2
In the past decade, we have witnessed an enormous growth in the demand for online video services. Recent studies estimate that nowadays, more than 1% of the global greenhouse gas e…
Jointly Resampling and Reconstructing Corrupted Images for Image Classification using Frequency-Selective Mesh-to-Grid Resampling
Viktoria Heimann, Andreas Spruck, André Kaup
Neural networks became the standard technique for image classification throughout the last years. They are extracting image features from a large number of images in a training pha…
Sweet Streams are Made of This: The System Engineer's View on Energy Efficiency in Video Communications
Christian Herglotz, Matthias Kränzler, Robert Schober +1
In recent years, the global use of online video services has increased rapidly. Today, a manifold of applications, such as video streaming, video conferencing, live broadcasting, a…
Increasing the Accuracy of a Neural Network Using Frequency Selective Mesh-to-Grid Resampling
Andreas Spruck, Viktoria Heimann, André Kaup
Neural networks are widely used for almost any task of recognizing image content. Even though much effort has been put into investigating efficient network architectures, optimizer…
Matched Quality Evaluation of Temporally Downsampled Videos with Non-Integer Factors
Christian Herglotz, Geetha Ramasubbu, André Kaup
Recent research has shown that temporal downsampling of high-frame-rate sequences can be exploited to improve the rate-distortion performance in video coding. However, until now, r…
A Comparative Analysis of the Time and Energy Demand of Versatile Video Coding and High Efficiency Video Coding Reference Decoders
Matthias Kränzler, Christian Herglotz, André Kaup
This paper investigates the decoding energy and decoding time demand of VTM-7.0 in relation to HM-16.20. We present the first detailed comparison of two video codecs in terms of so…
Extending Video Decoding Energy Models for 360° and HDR Video Formats in HEVC
Matthias Kränzler, Christian Herglotz, André Kaup
Research has shown that decoder energy models are helpful tools for improving the energy efficiency in video playback applications. For example, an accurate feature-based bit strea…
Advanced Design Space Exploration for Joint Energy and Quality Optimization for VVC
Matthias Kränzler, Christian Herglotz, André Kaup
In recent studies, it could be shown that the energy demand of Versatile Video Coding (VVC) decoders can be twice as high as comparable High Efficiency Video Coding (HEVC) decoders…
Hyperspectral Image Reconstruction from Multispectral Images Using Non-Local Filtering
Frank Sippel, Jürgen Seiler, André Kaup
Using light spectra is an essential element in many applications, for example, in material classification. Often this information is acquired by using a hyperspectral camera. Unfor…
Spatio-spectral Image Reconstruction Using Non-local Filtering
Frank Sippel, Jürgen Seiler, André Kaup
In many image processing tasks it occurs that pixels or blocks of pixels are missing or lost in only some channels. For example during defective transmissions of RGB images, it may…
Modeling the HEVC Encoding Energy Using the Encoder Processing Time
Geetha Ramasubbu, André Kaup, Christian Herglotz
The global significance of energy consumption of video communication renders research on the energy need of video coding an important task. To do so, usually, a dedicated setup is…
Optimized Decoding-Energy-Aware Encoding in Practical VVC Implementations
Matthias Kränzler, Adam Wieckowski, Geetha Ramasubbu +4
The optimization of the energy demand is crucial for modern video codecs. Previous studies show that the energy demand of VVC decoders can be improved by more than 50% if specific…
Rate-Distortion Optimal Transform Coefficient Selection for Unoccupied Regions in Video-Based Point Cloud Compression
Christian Herglotz, Nils Genser, André Kaup
This paper presents a novel method to determine rate-distortion optimized transform coefficients for efficient compression of videos generated from point clouds. The method exploit…
Evaluation of Video Coding for Machines without Ground Truth
Kristian Fischer, Markus Hofbauer, Christopher Kuhn +2
In the emerging field of video coding for machines, video datasets with pristine video quality and high-quality annotations are required for a comprehensive evaluation. However, ex…
Increasing Imaging Resolution by Non-Regular Sampling and Joint Sparse Deconvolution and Extrapolation
Jürgen Seiler, Markus Jonscher, Thomas Ussmueller +1
Increasing the resolution of image sensors has been a never ending struggle since many years. In this paper, we propose a novel image sensor layout which allows for the acquisition…
Automatic Registration of Images with Inconsistent Content Through Line-Support Region Segmentation and Geometrical Outlier Removal
Ming Zhao, Yongpeng Wu, Shengda Pan +3
The implementation of automatic image registration is still difficult in various applications. In this paper, an automatic image registration approach through line-support region s…
Learning-based Lossless Point Cloud Geometry Coding using Sparse Tensors
Dat Thanh Nguyen, Andre Kaup
Most point cloud compression methods operate in the voxel or octree domain which is not the original representation of point clouds. Those representations either remove the geometr…
Key Point Agnostic Frequency-Selective Mesh-to-Grid Image Resampling using Spectral Weighting
Viktoria Heimann, Nils Genser, André Kaup
Many applications in image processing require resampling of arbitrarily located samples onto regular grid positions. This is important in frame-rate up-conversion, super-resolution…
Saliency-Driven Versatile Video Coding for Neural Object Detection
Kristian Fischer, Felix Fleckenstein, Christian Herglotz +1
Saliency-driven image and video coding for humans has gained importance in the recent past. In this paper, we propose such a saliency-driven coding framework for the video coding f…