nils-herrmann/clean_scirepeval huggingface dataset:
JPEG XT: A Compression Standard for HDR and WCG Images [Standards in a Nutshell]

High bit depth data acquisition and manipulation have been largely studied at the academic level over the last 15 years and are rapidly attracting interest at the industrial level. An example of the increasing interest for high-dynamic range (HDR) imaging is the use of 32-bit floating point data for video and image acquisition and manipulation that allows a variety of visual effects that closely mimic the real-world visual experience of the end user  . At the industrial level, we are witnessing increasing traction toward supporting HDR and wide color gamut (WCG). WCG leverages HDR for each color channel to display a wider range of colors. Consumer cameras are currently available with a 14- or 16-bit analog-to-digital converter. Rendering devices are also appearing with the capability to display HDR images and video with a peak brightness of up to 4,000 nits and to support WCG (ITU-R Rec. BT.2020 ) rather than the historical ITU-R Rec. BT.709 . This trend calls for a widely accepted standard for higher bit depth support that can be seamlessly integrated into existing products and applications. While standard formats such as the Joint Photographic Experts Group (JPEG) 2000  and JPEG XR [6] offer support for high bit depth image representations, their adoption requires a nonnegligible investment that may not always be affordable in existing imaging ecosystems, and induces a difficult transition, as they are not backward-compatible with the popular JPEG image format.
Experimental Study on Superconducting Level Sensors in Liquid Helium

An approach for experimental investigation of the optimum sensor current of a superconducting level sensor is established and is then used for the investigation of the same of a NbTi and a MgB2/SS level sensors in liquid helium. On comparing the experimental results with that of the computational model established earlier, to simulate the operation of a superconducting level sensor, it was found that both agree closely. This shows the validity of the computational model for the characterization of a superconducting level sensor. Further on, the operation of these level sensors in a two-current method was studied. The results showed a higher heat load and level measurement time. However, it indicated an opportunity of retaining the linearity of the voltage versus liquid level curve even under high boil-off rate inside the cryostat. To scrutinize these findings, the NbTi level sensor operation in liquid helium was studied up to a boil-off rate of 5.77 g/s. It was observed that the sensor operation was not affected; however, the two-current method showed a more accurate level measurement compared to the one-current method.
Temporal Scalability of Dynamic Volume Data Using Mesh Compensated Wavelet Lifting

Due to their high resolution, dynamic medical 2D+t and 3D+t volumes from computed tomography (CT) and magnetic resonance tomography (MR) reach a size which makes them very unhandy for teleradiologic applications. A lossless scalable representation offers the advantage of a down-scaled version which can be used for orientation or previewing, while the remaining information for reconstructing the full resolution is transmitted on demand. The wavelet transform offers the desired scalability. A very high quality of the lowpass sub-band is crucial in order to use it as a down-scaled representation. We propose an approach based on compensated wavelet lifting for obtaining a scalable representation of dynamic CT and MR volumes with very high quality. The mesh compensation is feasible to model the displacement in dynamic volumes which is mainly given by expansion and contraction of tissue over time. To achieve this, we propose an optimized estimation of the mesh compensation parameters to optimally fit for dynamic volumes. Within the lifting structure, the inversion of the motion compensation is crucial in the update step. We propose to take this inversion directly into account during the estimation step and can improve the quality of the lowpass sub-band by 0.63 and 0.43 dB on average for our tested dynamic CT and MR volumes at the cost of an increase of the rate by 2.4% and 1.2% on average.
Coherent Subcarrier Processing Node Based on Optical Frequency Conversion and Free-Running Lasers

We demonstrate the use of frequency conversion in optical fiber to implement a coherent add/drop architecture. Its application is experimentally investigated in an optical frequency-division multiplexing scenario with up to three subcarriers which are modulated by quadrature phase-shift keying. We show subcarrier drop and replacement in a bus topology. Furthermore, we quantify tolerances with respect to delay and amplitude mismatch by experiments and simulations. Finally, we discuss on the scalability of the scheme.
Backwards Compatible Coding of High Dynamic Range Images with JPEG

In its Paris meeting, the JPEG committee decided to work on a backwards compatible extension of the popular JPEG (10918-1) standard enabling lossy and lossless coding of high-dynamic range (HDR) images, the new standard shall allow legacy applications to decompress new code streams into a tone mapped version of the HDR image while codecs aware of the extensions will decompress the stream with full dynamic range. This paper proposes a set of extensions that have rather low implementation complexity, and use - whenever possible - functional design blocks already present in 10918-1. It is seen that, despite its simplicity, the proposed extension performs close to JPEG 2000 (15444-2) and JPEG XR (29199-2) on the HDR test image set of the JPEG for high bit-rates.
Real-time photometric registration from arbitrary geometry

Visually coherent rendering for augmented reality is concerned with seamlessly blending the virtual world and the real world in real-time. One challenge in achieving this is the correct handling of lighting. We are interested in applying real-world light to virtual objects, and compute the interaction of light between virtual and real. This implies the measurement of the real-world lighting, also known as photometric registration. So far, photometric registration has mainly been done through capturing images with artificial light probes, such as mirror balls or planar markers, or by using high dynamic range cameras with fish-eye lenses. In this paper, we present a novel non-invasive system, using arbitrary scene geometry as a light probe for photometric registration, and a general AR rendering pipeline supporting real-time global illumination techniques. Based on state of the art real-time geometric reconstruction, we show how to robustly extract data for photometric registration to compute a realistic representation of the real-world diffuse lighting. Our approach estimates the light from observations of the reconstructed model and is based on spherical harmonics, enabling plausible illumination such as soft shadows, in a mixed virtual-real rendering pipeline.
Performance Evaluation of a Silicon Waveguide for Phase Regeneration of a QPSK Signal

In this paper a silicon-on-insulator nanorib waveguide with reverse-biased p-i-n-junction is used to experimentally demonstrate phase-sensitive amplification based on four-wave mixing for the realization of an in-line four-level phase-regenerator. Phase regeneration of a 14-GBd quadrature phase-shift keying signal is demonstrated for the first time employing a silicon waveguide as phase sensitive amplifier. The regenerator is placed in a 1040-km dispersion-managed link and it is shown that phase noise accumulation in the transmission link can be reduced by the use of the in-line silicon-based phase-regeneration.
ViPLab — An online programming lab

ViPLab is a virtual online programming laboratory for the ILIAS learning management system, developed by the University of Stuttgart and in active use for many years. ViPLab allows students to conduct their homeworks or electronic exams on personal devices in multiple programming languages requiring a browser as only local software installation. ViPLab also enables teachers to grade submitted solutions automatically. It supports multiple programming languages, MatLab/Octave, Java, C, C++ and DuMuX, with the option of adding additional languages when required.
High Dynamic Range Imaging Technology [Lecture Notes]

In this lecture note, we describe high dynamic range (HDR) imaging systems. Such systems are able to represent luminances of much larger brightness and, typically, a larger range of colors than conventional standard dynamic range (SDR) imaging systems. The larger luminance range greatly improves the overall quality of visual content, making it appear much more realistic and appealing to observers. HDR is one of the key technologies in the future imaging pipeline, which will change the way the digital visual content is represented and manipulated today.
Centroid adapted frequency selective extrapolation for reconstruction of lost image areas

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 lifting. The goal of image reconstruction is to restore these lost image areas as close to the original as possible. Frequency selective extrapolation is a block-based method for efficiently reconstructing lost areas in images. So far, the actual shape of the lost area is not considered directly. We propose a centroid adaption to enhance the existing frequency selective extrapolation algorithm that takes the shape of lost areas into account. To enlarge the test set for evaluation we further propose a method to generate arbitrarily shaped lost areas. On our large test set, we obtain an average reconstruction gain of 1.29 dB.
Coherent-Optical In-Line Add/Drop of PDM Tributaries of Subcarrier Multiplexed Signals

We propose an extended coherent optical add/drop multiplexing scheme, in which an individual polarization tributary in a polarization-division multiplexed orthogonal frequency-division multiplexed signal is erased and added by frequency conversion in fiber, which is sequentially inserted in a transmission line. In the scheme, a polarization tributary can be inserted and replaced in a dual polarization spectrally overlapped ultra-dense multiplexed signal. In a proof-of-concept demonstration, we investigate the performance of the proposed optical add/drop multiplexing scheme. A 25-Gb/s quadrature phase-shift keying tributary within a dual-polarization three subcarrier orthogonal frequency division multiplexed signal is erased and added with negligible distortion of the orthogonal polarization tributary and the adjacent subcarriers.
Super-resolution for mixed-resolution multiview image plus depth data using a novel two-stage high-frequency extrapolation method for occluded areas

Mixed-resolution multiview setups offer great savings in both, costs regarding the equipment acquisition and complexity refering to data transmission and storage. However, for applications like free viewpoint television, high-resolution images are desired from all available camera perspectives. Therefore, high-frequency information of adjacent high-resolution cameras can be used to increase the visual quality of a low-resolution camera perspective. However, due to occlusions, some parts of the scene are invisible in the high-resolution views and cannot be synthesized from the reference images. In this paper, a novel high-frequency extrapolation method is proposed, utilizing additional sampling points pre-estimated by a low-resolution block-matching approach. Averaged over all considered test sets, the proposed method achieves a PSNR gain of 0.94 dB with respect to the unrefined signal extrapolation algorithm.
THz-Range Optical Frequency Shifter for Dual Polarization WDM Signals Using Frequency Conversion in Fiber

We propose an optical frequency shifter for dual-polarization signals using frequency conversion in fiber. The proposed optical frequency shifter is achieved by transmitting input signal combined with two orthogonally polarized continuous wave pump lights through a nonlinear fiber and a polarizer. In the scheme, a polarization switched and frequency shifted copy of an original signal is generated in the nonlinear fiber and the subsequent polarizer removes the original signal in a wavelength independent fashion. It allows a fractional bandwidth shift, in which the shifted signal is overlapped with the original signal. We achieve THz range frequency shift with original signal suppression without an optical filter by using a polarization diversity loop. A polarization beam splitter is used as a splitter and a combiner of the loop as well as for original signal rejection. A contention resolution of two dual-polarization 400-Gb/s superchannels is demonstrated by applying the optical frequency shifter with acceptable in-band crosstalk. For any-to-any optical frequency shift, wavelength arrangement for pumps and required zero dispersion and dispersion slope of nonlinear fibers are numerically simulated.
3-D mesh compensated wavelet lifting for 3-D+t medical CT data

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 can lead to disturbing artifacts. By incorporating feasible compensation methods directly into the wavelet transform, the quality of the lowpass band can be improved. The displacement in dynamic medical 3-D+t volumes from Computed Tomography is mainly given by expansion and compression of tissue over time and can be modeled well by mesh-based methods. We extend a 2-D mesh-based compensation method to three dimensions to obtain a volume compensation method that can additionally compensate deforming displacements in the third dimension. 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. Results from lossless coding with JPEG 2000 3D and SPECK3D show that the compensated subbands using a 3-D mesh need about 6% less data compared to using a 2-D mesh.
Efficient ultra-fast all-optical wavelength converters with Ti:PPLN waveguides

Applications of packaged and pigtailed (tunable) integrated all-optical Ti:PPLN wavelength converters (AOWC) with different modulation formats (RZ-DQPSK, 16-ary QAM) are reported. The devices take advantage of cascaded second order nonlinear interactions allowing tuning with either one or two control waves via cSHG/DFG or cSFG/DFG. Operation of polarization insensitive AOWCs on a variety of presented high-bit-rate (up to 320 Gb/s) transmission experiments and mid-span chromatic dispersion compensation in the C-band with negligible penalties promises great potential for application in transparent all-optical networks (TAON). In addition recent progress with respect to bandwidth and efficiency of the cSHG/DFG-based wavelength converters is reported. The efficiency is increased by pump-resonant wavelength conversion and by increased interaction length in a phase controlled double-pass scheme.
Individualization and Flexibility through Computer Algebra Systems in Virtual Laboratories

Virtual labs enable field specific experiments and open them for collaborative and distributed usage. In order to realize comprehensive laboratory set-ups providing a scientific broadness and user adaptivity, several challenges regarding the integration of different software technologies have to be solved. We propose an eLearning framework consisting of a learner and a course model; exercises within this framework are supplemented by virtual laboratories and computer algebra systems. We discuss the potentials of this setup on the example of the laboratory VideoEasel and its interface to Maple
Robust Nailfold Capillary Skeleton Extraction

Nail fold capillaroscopy (NC) an inexpensive, non-invasive method to assess capillary morphology, and is routinely used for the detection of scleroderma spectral disorders, Raynaud's phenomenon and other connective tissue diseases. Evaluation of NC requires expert knowledge and is typically performed by careful manual inspection of the images. Computer-aided approaches of capillary inspection would reduce the time required for diagnosis but have been little pursued due to the challenges present in NC images. In this paper, we present a capillary skeletonisation algorithm based on image enhancement followed by binarisation and skeleton extraction using a thinning algorithm. The extracted vessel skeleton can subsequently be utilised for auto measurement of capillary density and other parameters. We demonstrate that our algorithm works well and that it clearly outperforms previous approaches.
A Multi-resolution Action Recognition Algorithm Using Wavelet Domain Features

This paper proposes a novel approach for human action recognition using multi-resolution feature extraction based on the two-dimensional discrete wavelet transform (2D-DWT). Action representations can be considered as image templates, which can be useful for understanding various actions or gestures as well as for recognition and analysis. An action recognition scheme is developed based on extracting features from the frames of a video sequence. The proposed feature selection algorithm offers the advantage of very low feature dimensionality and therefore lower computational burden. It is shown that the use of wavelet-domain features enhances the distinguish ability of different actions, resulting in a very high within-class compactness and between-class separability of the extracted features, while certain undesirable phenomena, such as camera movement and change in camera distance from the subject, are less severe in the frequency domain. Principal component analysis is performed to further reduce the dimensionality of the feature space. Extensive experimentations on a standard benchmark database confirm that the proposed approach offers not only computational savings but also a very recognition accuracy.
Robust estimation of the fundamental matrix

Most approaches to estimate the fundamental matrix assume a Gaussian distribution in the errors in view of mathematical tractability. However, this assumption is violated if the distribution computed is not normal. In this paper we propose a robust approach of estimating the fundamental matrix which does not rely on the Gaussian assumption. The proposed technique, weighted least squares (WLS), is the application of linear mixed-effects models considering the correlation between different data sub-samples. It provides an unbiased estimation of the fundamental matrix which is not affected by outlier samples. Experimental results on synthetic and real images confirm the accuracy of our method and its superiority to standard estimation methods.
JIRL - A C++ Library for JPEG Compressed Domain Image Retrieval

In this paper we present JIRL, an open source C++ software suite that allows to perform content-based image retrieval in the JPEG compressed domain. We provide implementations of nine retrieval algorithms representing the current state-of-the-art. For each algorithm, methods for compressed domain feature extraction as well as feature comparison are provided in an object-oriented framework. In addition, our software suite includes functionality for benchmarking retrieval algorithms in terms of retrieval performance and retrieval time. An example full image retrieval application is also provided to demonstrate how the library can be used. JIRL is made available to fellow researchers under the LGPL.
Data Mining of Gene Expression Data by Fuzzy and Hybrid Fuzzy Methods

Microarray studies and gene expression analysis have received tremendous attention over the last few years and provide many promising avenues toward the understanding of fundamental questions in biology and medicine. Data mining of these vasts amount of data is crucial in gaining this understanding. In this paper, we present a fuzzy rule-based classification system that allows for effective analysis of gene expression data. The applied classifier consists of a set of fuzzy if-then rules that enable accurate nonlinear classification of input patterns. We further present a hybrid fuzzy classification scheme in which a small number of fuzzy if-then rules are selected through means of a genetic algorithm, leading to a compact classifier for gene expression analysis. Extensive experimental results on various well-known gene expression datasets confirm the efficacy of our approaches.
Application of neural networks for modelling centrifugal pumping units of booster pump stations for a two-phase gas-liquid mixture

In this paper, we investigate operational principles of booster pump stations with the aim of developing a method to calculate the influence of the cross-sectional shape of the channel on the coefficient of hydraulic friction and the effect of the curvature of the fixed channel on the coefficient of hydraulic friction and influence of rotation on the coefficient of hydraulic resistance for cylindrical rectilinear channel and border conditions. In this context, we propose the application of neural networks to build a model of centrifugal pumping units of booster pump stations for a two-phase gas-liquid mixture.
Texture Classification Using Multi-dimensional LBP Variance

Texture classification is an important task for a variety of computer vision applications. A successful group of texture algorithms based on local neighbourhood descriptors and known as LBP (local binary patterns) has been shown to provide good and robust discriminative power, and is typically applied in a rotation invariant form and calculated at multiple resolutions. Local contrast information can be integrated into the LBP histogram generation by using the variance as weights for LBP, leading to LBP variance (LBPV) texture features. Multi-scale LBPV histograms are obtained by concatenating the individual one-dimensional histograms derived from each scale. In this paper, we show that by calculating a multi-dimensional LBP variance (MD-LBPV) histogram improved texture classification can be achieved. We confirm this based on extensive experiments on several Outex benchmark datasets.
Retinal vessel segmentation based on possibilistic fuzzy c-means clustering optimised with cuckoo search

Automated analysis of retinal vessels is essential for the diagnosis of a wide range of eye diseases and plays an important role in automatic retinal disease screening systems. In this paper, we present an approach to automatic vessel segmentation in retinal images that utilises possibilistic fuzzy c-means (PFCM) clustering to overcome the problems of the conventional fuzzy c-means objective function. In order to obtain optimised clustering results using PFCM, a cuckoo search method is used. The cuckoo search algorithm, which is based on the brood parasitic behaviour of some cuckoo species in combination with the Levy flight behaviour of some birds and fruit flies, is applied to drive the optimisation of the fuzzy clustering. The performance of our algorithm is analysed on two benchmark databases, the DRIVE and STARE datasets, and encouraging segmentation performance is observed.
Quality Metric Based Colour Palette Optimisation

Colour quantisation is a common image processing technique where full colour images are to be displayed using a limited palette. The choice of a good palette is therefore crucial as it directly determines the quality of the resulting image. Standard quantisation approaches typically try to minimise the (squared) error between the original and the quantised image which does not correspond well to how humans perceive the images. In this paper we introduce a new colour quantisation algorithm that is designed not to minimise these errors but to maximise the image quality as evaluated by S-CIELAB, an image quality metric that has been shown to work well for various image processing tasks. Experimental results based on a set of standard images demonstrate the superiority in terms of achieved image quality of our novel method.