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Found 70 papers, 4 papers with code
Color Agnostic Cross-Spectral Disparity Estimation
The theoretical examination of the novel color agnostic method is completed by an extensive evaluation compared to state of the art including self-recorded multispectral data and a reference implementation.
A Guided Upsampling Network for Short Wave Infrared Images Using Graph Regularization
Thus, in this paper an upsampling method for SWIR images guided by a visible image is presented.
RGB-Guided Resolution Enhancement of IR Images
To this end, GIRRE increases the spatial resolution of the low-resolution IR image.
Conditional Residual Coding: A Remedy for Bottleneck Problems in Conditional Inter Frame Coding
Conditional coding is a new video coding paradigm enabled by neural-network-based compression.
Cross Spectral Image Reconstruction Using a Deep Guided Neural Network
Since only little cross spectral data is available for training, this neural network is highly regularized.
End-to-End Lidar-Camera Self-Calibration for Autonomous Vehicles
The network is arranged in a Siamese-twin structure to constrain the network features learning to a mutually shared feature in both point cloud and camera (Lidar-camera constraint).
Analysis of mesh-based motion compensation in wavelet lifting of dynamical 3-D+t CT data
Factorized in the lifting structure, the wavelet transform can easily be extended by arbitrary compensation methods.
Compression of Dynamic Medical CT Data Using Motion Compensated Wavelet Lifting with Denoised Update
For the lossless compression of dynamic 3-D+t volumes as produced by medical devices like Computed Tomography, various coding schemes can be applied.
Synthetic Hyperspectral Array Video Database with Applications to Cross-Spectral Reconstruction and Hyperspectral Video Coding
Two novel algorithms for two different applications are proposed to prove the diversity of applications that can be addressed by this novel database.
Centroid adapted frequency selective extrapolation for reconstruction of lost image areas
To enlarge the test set for evaluation we further propose a method to generate arbitrarily shaped lost areas.
Analysis of displacement compensation methods for wavelet lifting of medical 3-D thorax CT volume data
A huge advantage of the wavelet transform in image and video compression is its scalability.
On the influence of clipping in lossless predictive and wavelet coding of noisy images
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.
Efficient lossless coding of highpass bands from block-based motion compensated wavelet lifting using JPEG 2000
Lossless image coding is a crucial task especially in the medical area, e. g., for volumes from Computed Tomography or Magnetic Resonance Tomography.
3-D mesh compensated wavelet lifting for 3-D+t medical CT data
We show that a 3-D mesh can obtain a higher quality of the lowpass band by 0. 28 dB with less than 40% of the model parameters of a comparable 2-D mesh.
Improving block-based compensated wavelet lifting by reconstructing unconnected pixels
This paper presents a new approach for improving the visual quality of the lowpass band of a compensated wavelet transform.
A hybrid motion estimation technique for fisheye video sequences based on equisolid re-projection
Capturing large fields of view with only one camera is an important aspect in surveillance and automotive applications, but the wide-angle fisheye imagery thus obtained exhibits very special characteristics that may not be very well suited for typical image and video processing methods such as motion estimation.
Temporal error concealment for fisheye video sequences based on equisolid re-projection
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 concealment.
Domain Adaptation for Unknown Image Distortions in Instance Segmentation
However, in practice unknown distortion can lead to a domain gap between training and test data, impeding the performance of a machine vision system.
Synthesizing Annotated Image and Video Data Using a Rendering-Based Pipeline for Improved License Plate Recognition
The benefits of the proposed data generation pipeline, especially for machine learning scenarios with limited available training data, are demonstrated by an extensive experimental validation in the context of automatic license plate recognition.
3D Rendering Framework for Data Augmentation in Optical Character Recognition
Applying the proposed method, improvements of up to 2. 79 percentage points in terms of Character Error Rate (CER), and up to 7. 88 percentage points in terms of Word Error Rate (WER) are achieved on the subset.
Quality Assurance of Weld Seams Using Laser Triangulation Imaging and Deep Neural Networks
Due to their special characteristics, the images must be pre-processed to enable the use of a deep neural network.
Optimal Filter Selection for Multispectral Object Classification Using Fast Binary Search
In this paper we introduce a novel fast binary search for optimal filter selection that guarantees a minimum distance metric between the different spectra to classify.
Structure-Preserving Spectral Reflectance Estimation using Guided Filtering
This novel estimation method is based on the guided filtering technique which preserves basic structures, while using spatial information to reduce the influence of noise.
Spatio-spectral Image Reconstruction Using Non-local Filtering
In many image processing tasks it occurs that pixels or blocks of pixels are missing or lost in only some channels.
Hyperspectral Image Reconstruction from Multispectral Images Using Non-Local Filtering
Therefore, multispectral cameras with wide-band filters are used, which are much cheaper and are often able to capture videos.
Motion-Adapted Three-Dimensional Frequency Selective Extrapolation
This proposed extension solves the problem of changing content within the area considered by the 3D-FSE, which is caused by motion within the sequence.
Forensic License Plate Recognition with Compression-Informed Transformers
Forensic license plate recognition (FLPR) remains an open challenge in legal contexts such as criminal investigations, where unreadable license plates (LPs) need to be deciphered from highly compressed and/or low resolution footage, e. g., from surveillance cameras.
Spatio-temporal prediction in video coding by best approximation
Within the scope of this contribution we propose a novel efficient spatio-temporal prediction algorithm for video coding.
Optimized processing order for 3D hole filling in video sequences using frequency selective extrapolation
A problem often arising in video communication is the reconstruction of missing or distorted areas in a video sequence.
Spatio-temporal prediction in video coding by non-local means refined motion compensation
For this, the prediction is carried out in two steps.
Orthogonality Deficiency Compensation for Improved Frequency Selective Image Extrapolation
Therefore the signal from the known samples is iteratively projected onto different basis functions in order to generate a model of the signal.
Adaptive frequency prior for frequency selective reconstruction of images from non-regular subsampling
The proposed adaptive prior allows for a very high reconstruction quality, yielding gains of up to 0. 6 dB PSNR over the fixed prior, independently of the density of the available samples.
Adaptive joint spatio-temporal error concealment for video communication
In the past years, video communication has found its application in an increasing number of environments.
Multiple Selection Extrapolation for Improved Spatial Error Concealment
This contribution introduces a novel signal extrapolation algorithm and its application to image error concealment.
Spatio-temporal prediction in video coding by spatially refined motion compensation
The purpose of this contribution is to introduce a new method of signal prediction in video coding.
Content-Adaptive Motion Compensated Frequency Selective Extrapolation for Error Concealment in Video Communication
To cope with this, error concealment can be applied on the distorted data at the receiver.
Spatio-temporal error concealment in video by denoised temporal extrapolation refinement
For this, Non-Local Means denoising is used which is extended by a spiral scan processing order and is improved by an adaptation step for taking the preliminary temporal extrapolation into account.
Multiple Selection Approximation for Improved Spatio-Temporal Prediction in Video Coding
In this contribution, a novel spatio-temporal prediction algorithm for video coding is introduced.
Fast orthogonality deficiency compensation for improved frequency selective image extrapolation
Since the basis functions are not orthogonal regarding the area of the known samples, the projection does not lead to the real portion a basis function has of the signal.
Reusing the H.264/AVC deblocking filter for efficient spatio-temporal prediction in video coding
The prediction step is a very important part of hybrid video codecs for effectively compressing video sequences.
Distributed Parallel Image Signal Extrapolation Framework using Message Passing Interface
The proposed framework allows for the application of existing image signal extrapolation algorithms without the need to modify them for a parallel processing.
Motion Compensated Frequency Selective Extrapolation for Error Concealment in Video Coding
Although wireless and IP-based access to video content gives a new degree of freedom to the viewers, the risk of severe block losses caused by transmission errors is always present.
Optimized and Parallelized Processing Order for Improved Frequency Selective Signal Extrapolation
In this contribution an optimized processing order is proposed for Frequency Selective Extrapolation, a powerful signal extrapolation algorithm.
Denoising-based image reconstruction from pixels located at non-integer positions
Digital images are commonly represented as regular 2D arrays, so pixels are organized in form of a matrix addressed by integers.
Scalable Kernel-Based Minimum Mean Square Error Estimator for Accelerated Image Error Concealment
In this paper, we propose a novel scalable spatial error concealment algorithm that aims at obtaining high quality reconstructions with reduced computational burden.
Reliability-based Mesh-to-Grid Image Reconstruction
This paper presents a novel method for the reconstruction of images from samples located at non-integer positions, called mesh.
Frequency selective extrapolation with residual filtering for image error concealment
The purpose of signal extrapolation is to estimate unknown signal parts from known samples.
Fast Reconstruction of Three-Quarter Sampling Measurements Using Recurrent Local Joint Sparse Deconvolution and Extrapolation
Recently, non-regular three-quarter sampling has shown to deliver an increased image quality of image sensors by using differently oriented L-shaped pixels compared to the same number of square pixels.
Resampling Images to a Regular Grid from a Non-Regular Subset of Pixel Positions Using Frequency Selective Reconstruction
Even though image signals are typically defined on a regular two-dimensional grid, there also exist many scenarios where this is not the case and the amplitude of the image signal only is available for a non-regular subset of pixel positions.
Increasing Imaging Resolution by Non-Regular Sampling and Joint Sparse Deconvolution and Extrapolation
In this paper, we propose a novel image sensor layout which allows for the acquisition of images at a higher resolution and improved quality.
Motion Compensated Three-Dimensional Frequency Selective Extrapolation for Improved Error Concealment in Video Communication
The model generation is conducted by an enhanced version of Three-Dimensional Frequency Selective Extrapolation, an existing error concealment algorithm.
Complex-Valued Frequency Selective Extrapolation for Fast Image and Video Signal Extrapolation
Within the scope of this contribution, we introduce the complex-valued Frequency Selective Extrapolation for fast image and video signal extrapolation.
A Fast Algorithm for Selective Signal Extrapolation with Arbitrary Basis Functions
Within the scope of this contribution, a novel efficient solution for Selective Extrapolation is presented for utilization with arbitrary basis functions.
Reconstruction of images taken by a pair of non-regular sampling sensors using correlation based matching
Recently, it has been shown that by covering a low resolution sensor with a non-regular sampling mask and by using an efficient algorithm for image reconstruction, a high resolution image can be obtained.
Reconstruction of Videos Taken by a Non-Regular Sampling Sensor
Recently, it has been shown that a high resolution image can be obtained without the usage of a high resolution sensor.
Reducing Randomness of Non-Regular Sampling Masks for Image Reconstruction
Recently, it has been shown that it is possible to obtain a high resolution image by covering a low resolution sensor with a non-regular sampling mask.
Declipping of Speech Signals Using Frequency Selective Extrapolation
The reconstruction of clipped speech signals is an important task in audio signal processing to achieve an enhanced audio quality for further processing.
Dynamic Non-Regular Sampling Sensor Using Frequency Selective Reconstruction
The main benefit of the proposed dynamic readout is that for each frame, different sampling points are available which is advantageous since this information can significantly enhance the reconstruction quality of the proposed reconstruction algorithm.
Texture-Dependent Frequency Selective Reconstruction of Non-Regularly Sampled Images
Hence, a new texture-dependent approach for frequency selective reconstruction is introduced that distributes the number of iterations depending on the texture of the regions to be reconstructed.
Recursive Frequency Selective Reconstruction of Non-Regularly Sampled Video Data
In this paper, a new recursive multi-frame reconstruction approach is proposed in order to further increase the reconstruction quality.
Novel Consistency Check For Fast Recursive Reconstruction Of Non-Regularly Sampled Video Data
Altogether, we are able to significantly increase the reconstruction quality by + 1. 01 dB compared to the state-of-the-art recursive reconstruction method using a fixed mask.
Estimation of Non-Functional Properties for Embedded Hardware with Application to Image Processing
In recent years, due to a higher demand for portable devices, which provide restricted amounts of processing capacity and battery power, the need for energy and time efficient hard- and software solutions has increased.
Enhanced Image Reconstruction From Quarter Sampling Measurements Using An Adapted Very Deep Super Resolution Network
Quarter sampling is a novel sensor concept that enables the acquisition of higher resolution images without increasing the number of pixels.
Iterative Optimization of Quarter Sampling Masks for Non-Regular Sampling Sensors
Non-regular sampling can reduce aliasing at the expense of noise.
Design Techniques for Incremental Non-Regular Image Sampling Patterns
Even though image signals are typically acquired on a regular two dimensional grid, there exist many scenarios where non-regular sampling is possible.
Real-Time Frequency Selective Reconstruction through Register-Based Argmax Calculation
Frequency Selective Reconstruction (FSR) is a state-of-the-art algorithm for solving diverse image reconstruction tasks, where a subset of pixel values in the image is missing.
Generalized Difference Coder: A Novel Conditional Autoencoder Structure for Video Compression
Motion compensated inter prediction is a common component of all video coders.
Image Super-Resolution Using T-Tetromino Pixels
Next, we investigate the reconstruction quality using tetromino pixels for the first time in literature.
Sparse Signal Reconstruction with Multiple Side Information using Adaptive Weights for Multiview Sources
This two-level optimization leads the proposed reconstruction algorithm with multiple SI using adaptive weights (RAMSIA) to robustly exploit the multiple SIs with different qualities.
Concept for a CMOS Image Sensor Suited for Analog Image Pre-Processing
As an example, an image restoration algorithm for reducing image noise is applied as image pre-processing in the analog domain.
