nils-herrmann/clean_scirepeval huggingface dataset:
Methodology for design of antialiasing filters for autostereoscopic displays

Multi-view autostereoscopic displays can be modelled as a multirate system. The design of such displays involves a construction compromise between the amount of different views and the spatial resolution of each view. Images to be visualised on these displays are prone to aliasing errors. Careful antialiasing requires knowledge about the display frequency response, which is determined mainly by the view sub-sampling topology but it is also influenced by some other, generally non-linear, aliasing-causing display effects. In this work, a methodology for designing antialiasing filters for autostereoscopic displays is proposed. It includes the following three steps: (i) measuring aliasing effects by a set of test images – displayed on the screen, then photographed and then analysed in Fourier domain; (ii) estimating the display passband based on the set of measurements and (iii) designing filters confined to the so-estimated band. Using this methodology, one non-separable and three separable antialiasing filters have been designed. The non-separable filter cancels the aliasing terms completely, whereas the separable approximations allow for some small amount of aliasing for the sake of perceptually favoured sharpness preservation. The advantage of the methodology with respect to previously suggested antialiasing filter design approaches is demonstrated by objective comparisons of filter performance and computational efficiency and by visual inspection on a set of test images.
Joint de-noising and fusion of 2D video and depth map sequences sensed by low-powered tof range sensor

We propose a joint de-noising and data fusion approach where the fused modalities come from conventional high-resolution photo or video camera and low-resolution range sensor of Time-of-flight (ToF) type, operating in restricted conditions of low-emitting power and low number of sensor elements. Our approach includes identifying the various noise sources and suggesting suitable remedies at particular stages of data sensing and fusion. More specifically, fixed pattern noise and system noise are treated at a preliminary denoising stage working on range data only. In contrast to other 2D video/depth fusion approaches, which suggest working in planar coordinates, our approach includes additional denoising refinement in the space of 3D world coordinate system (i.e. point cloud space). Furthermore, the high-resolution grid resampling is performed as an iterative non-uniform to uniform resampling based on the Richardson method. This improves the performance compared to approaches based on low-to-high grid upsampling and subsequent refinement. We report experimental results where the achieved quality of fused data is the same as if the ToF sensor was operating in normal (low-noise) sensing mode.
Performance Assessment of A Diffraction Field Computation Method Based on Source Model

Efficient computation of scalar optical diffraction field due to an object is an essential issue in holographic 3D television systems. The first step in the computation process is to construct an object. As a solution for this step, we assume that an object can be represented by a set of distributed data points over a space. The second step is to determine which algorithm provides better performance. The source model whose performance is investigated is based on superposition of the diffraction fields emanated from the hypothetical light sources located at the given sample points. Its performance is evaluated according to visual quality of the reconstructed field and its algorithmic complexity. Source model provides acceptable reconstructed patterns when the region in which the samples are given has a narrow depth along the longitudinal direction and a wide extent along the transversal directions. Also, the source model gives good results when the cumulative field at the location of each point due to all other sources tends to be independent of that location.
Crosstalk Measurement Methodology for Auto-Stereoscopic Screens

Autostereoscopic displays utilizing slanted lenticular sheets produce specific artifacts. These artifacts affect the perception of a 3D scene, and are caused by a process which can be modeled as inter-channel crosstalk. We propose methodology for measuring such a crosstalk for arbitrary multiview 3D display. The measured data might be used for optimizing multiview image sets for a given display.
Spline-based resampling of noisy images

We consider the problem of image resampling in the presence of noise in terms of a regularized solution for spline-like model coefficients. The properties of the generalized cross-validation (GCV) and the Akaike information criterion (AIC) for determination of the time number of the model coefficients and the value of the regularization parameter have been examined. A two-parameter optimization procedure can be applicable in the case of noisy resampling. The method is applicable when the image should be resampled and denoised at the same time. The problem is somehow related to the problem of finding the natural scale of representation, when one aims to find the image scale optimum for further processing (compression, denoising, etc.). The practical realization of the method is discussed as well.
Analysis and optimization of pixel usage of light-field conversion from multi-camera setups to 3D light-field displays

Light-field (LF) 3D displays require vast amount of views representing the original scene when using pure light-ray interpolation to convert multi-camera content to display-specific LF representation. Synthetic and real multi-camera setups are both used to feed these displays with image-based data, however the layout, number, frustum, and resolution of these cameras are mostly suboptimal. Storage and transmission of LF data is an issue, especially considering that some of the captured / rendered pixels are left unused while generating the final image. LF displays can have significantly different requirements for camera setups due to differences in Field of View (FOV), angular resolution and spatial resolution. An analysis of typical camera setups and LF display setups, and the typical patterns in pixel usage resulting from the combination of these setups are presented. Based on this analysis, an optimization method for virtual camera setups is proposed. As virtual cameras have wide range of adjustment possibilities, highly optimized setups for specific displays can be achieved.
Accelerated Shearlet-Domain Light Field Reconstruction

We consider the problem of reconstructing densely sampled light field (DSLF) from sparse camera views. In our previous work, the DSLF has been reconstructed by processing epipolar-plane images (EPI) employing sparse regularization in shearlet transform domain. With the aim to avoid redundant processing and reduce the overall reconstruction time, in this paper, we propose algorithm modifications in three directions. First, we modify the basic algorithm by offering a faster and more stable iterative procedure. Second, we elaborate on the proper use of color redundancy by studying the effect of reconstruction of an average intensity channel and its use as a guiding mode for colorizing the three color channels. Third, we explore similarities between EPIs by their grouping and joint processing or by effective decorrelation to get an initial estimate for the basic iterative procedure. We are specifically interested in GPU-based computations allowing an efficient implementation of the shearlet transform. We quantify our three main approaches to accelerated processing over a wide collection of horizontal as well as full-parallax datasets.
Lossless compression of subaperture images using context modeling

The paper proposes a method for lossless compression of subaperture image stacks obtained by rectifying light-field images captured by a plenoptic camera. We exploit the similarities between two subaperture images using a predictive coding algorithm, where the current view is predicted from one reference view. Context modeling is the main technique used to reduce the image file size. A suitable image segmentation and a template context are used by the context tree algorithm for encoding up to the smallest detail in each subaperture image. Entropy coding is configured by a residual analysis module. The results show improved performance compared to the state-of-the-art encoders.
Multiple Description Coding of 3D Geometrywith Forward Error Correction Codes

This work presents a multiple description coding (MDC) scheme for compressed three dimensional (3D) meshes based on forward error correction (FEC). It allows flexible allocation of coding redundancy for reliable transmission over error-prone channels. The proposed scheme is based on progressive geometry compression, which is performed by using wavelet transform and modified SPIHT algorithm. The proposed algorithm is optimized for varying packet loss rates (PLR) and channel bandwidth. Modeling distortion-rate function considerably decreases computational complexity of bit allocation.
Fast hierarchical cost volume aggregation for stereo-matching

Some of the best performing local stereo-matching approaches use cross-bilateral filters for proper cost aggregation. The recent attempts have been directed toward efficient approximations of such filter aimed at higher speed. In this paper, we suggest a simple yet efficient coarse-to-fine cost volume aggregation scheme, which employs pyramidal decomposition of the cost volume followed by edge-avoiding reconstruction and aggregation. The scheme substantially reduces the computational complexity while providing fair quality of the estimated disparity maps compared to other approximated bilateral filtering schemes. In fact, the speed of the proposed technique is comparable with the speed of fixed kernel aggregation implemented through integral images.
Depth estimation by combining stereo matching and coded aperture

We investigate possible improvements that can be achieved in depth estimation by merging coded apertures and stereo cameras. We analyze several stereo camera setups which are equipped with different sets of coded apertures to explore such possibilities. The demonstrated results of this analysis are encouraging in the sense that coded apertures can provide valuable complementary information to stereo vision based depth estimation in some cases. In addition to that, we take advantage of stereo camera arrangement to have a single shot multiple coded aperture system. We show that with this system, it is possible to extract depth information robustly, by utilizing the inherent relation between the disparity and defocus cues, even for scene regions which are problematic for stereo matching.
Light Field Reconstruction Using Shearlet Transform

In this article we develop an image based rendering technique based on light field reconstruction from a limited set of perspective views acquired by cameras. Our approach utilizes sparse representation of epipolar-plane images (EPI) in shearlet transform domain. The shearlet transform has been specifically modified to handle the straight lines characteristic for EPI. The devised iterative regularization algorithm based on adaptive thresholding provides high-quality reconstruction results for relatively big disparities between neighboring views. The generated densely sampled light field of a given 3D scene is thus suitable for all applications which require light field reconstruction. The proposed algorithm compares favorably against state of the art depth image based rendering techniques and shows superior performance specifically in reconstructing scenes containing semi-transparent objects.
Bessel Functions-Based Reconstruction of Non-Uniformly Sampled Diffraction Fields

A discrete computational model for the diffraction process is essential in forward problems related to holographic TV. The model must be as general as possible, since the shape of the displayed objects does not bear any restrictions. We derive a discrete diffraction model which suits the problem of reconstruction of diffraction fields from a set of non-uniformly distributed samples. The only restriction of the model is the wave nature of the field. The derivation takes advantage of changing the spatial and frequency coordinates to polar form and ends up with a model stated in terms of Bessel functions. The model proves to be a separable orthogonal basis. It shows rapid convergence when evaluated in the framework of the non-uniform sampling problem.
Super resolution inverse imaging for plenoptic camera using wavefield modeling

A plenoptic camera consists of microlenses that enable the measuring of directional information. A common image formation model of the plenoptic camera is based on geometrical optics and provides an object reconstruction with a resolution equal to the number of microlenses. We use a more accurate model that takes into account the wave properties of light. A discrete formulation of this model is done in order to develop the inverse imaging technique which is efficient for super resolution object reconstruction even from noisy data. The proposed algorithm is based on a special modification of the IDD-BM3D deblurring algorithm. The achieved resolution highly exceeds the number of microlenses which is what we call super resolution imaging. Simulations show that the proposed strategy essentially outperforms the previously suggested method based on the wavefield modeling.
Noninvasive His-bundle electrocardiogram: toward beat-to-beat electromyogram noise removal

EMG noise is a very impeding factor for beat-to-beat detection of His micropotentials in high-resolution ECG. Its reduction was attempted by a two-stage wavelet-domain Wiener filtering procedure. In the first stage, a pilot signal estimate was obtained by averaging a rather small number (/spl sim/20) of successive beats synchronized to the R peak. In the second stage, this pilot signal together with EMG noise variance estimate, was used in the wavelet-domain Wiener filtering. The proposed noise suppression technique establishes a compromise between the need of beat-to-beat evaluation of the His potential and the noise-suppression-effective averaging. The algorithm shows adequate performance for records containing both moderate EMG and power-line interference, and for ECGs of sufficiently long P-Q interval (P-wave separated from Q-wave).
Simulation of microlens array based plenoptic capture utilizing densely sampled light field

Plenoptic cameras can capture the light field of a 3D scene in a single shot, which makes them attractive for several applications, such as depth estimation and refocusing. The difficulties in accurate calibration of available plenoptic camera designs, however, makes it also difficult to reliably assess such applications. This arises a need to have a ground-truth plenoptic data. We propose an accurate and efficient way to simulate the defocused plenoptic camera based on the geometric optics principles and the concept of densely sampled light field. In particular, we utilize the open-source computer graphics rendering software tool Blender and rely on a set of conventional 2D pinhole images of the scene captured from several viewpoints within the aperture of the main lens of the plenoptic camera. Elemental-image wise examination of plenoptic data and testing of post processing algorithms verifies the accuracy of the simulation.
Towards compound stereo-video quality metric: a specific encoder-based framework

We suggest a compound full-reference stereo-video quality metric composed of two components: a monoscopic quality component and stereoscopic quality component. While the former assesses the trivial monoscopic perceived distortions caused by blur, noise, contrast change etc., the latter assesses the perceived degradation of binocular depth cues only. We use the structural similarity index as a measure for perceptual similarity and design a multiscale algorithm for obtaining a perceptual disparity map and a stereo-similarity map to be used in the suggested metric. We verify the performance of the metric with subjective tests on distorted stereo images and coded stereo-video sequences with a final aim to build a perceptually-aware feedback for a H.264 based stereo-video encoder
A disparity range estimation technique for stereo-video streaming applications

In this paper, we propose a robust and efficient technique for frame-by-frame estimation of disparity ranges in stereo video. The proposed technique utilizes a single-layer image size reduction for faster processing and more effective noise handling. Furthermore, it applies spatial-domain non-linear filtering of both disparity and confidence maps for additional noise suppression and improved range estimation. A mechanism for supporting temporal consistency is proposed as well. Performance comparisons with recent approaches demonstrate the advantages of the proposed approach.
Influence Of camera imaging pipeline on stereo-matching quality: An experimental study

The paper aims at characterizing the role of camera capture process in depth quality estimation by stereo-matching methods. An evaluation software application has been developed which integrates a modular image processing pipeline (IPP) in to the depth estimation process. The application allows for simulating the presence of camera-specific processing artifacts and their influence on the captured stereo imagery in typical imaging scenarios. Furthermore, it allows for benchmarking and optimizing both the depth estimation module and camera capture settings for a jointly-optimal performance.
Stereoscopic Depth Cues Outperform Monocular Ones on Autostereoscopic Display

The aim of this study is two-fold; first, to compare how certain visual aids contribute in depth estimation tasks on a portable autostereoscopic display; and second, how these depth cues impact on perceived quality. These were studied on a quantitative subjective study using a portable autostereoscopic display in controlled laboratory environment. Test participants evaluated object depths on three-dimensional images, where either 2D cues, 3D cues, or their combinations were provided. The study was conducted using three different compression levels in order to study how image quality affects the perception of depth. The results indicate that the depth estimation task is faster conducted when the participants relied on stereoscopic depth cues compared to situations where only monocular cues were present. Also, depth estimation task is faster conducted with higher quality images. Depth estimation accuracy was also higher with stereoscopic depth cues than with monocular ones. These results suggest that the human visual system can make more reliable depth estimates on portable autostereoscopic displays when stereoscopic cues are present. However, the results of the quality evaluations indicate that, as stated also on previous studies, the added stereoscopic depth does not seem to increase the subjective image quality.
Juxtaposition between compression and depth for stereoscopic image quality on portable auto-stereoscopic display

Presence of depth and compression artifacts have been identified as major factors that influence subjective quality of experience and satisfaction of 3D imagery visualized on a portable auto-stereoscopic display. The juxtaposition between these two factors has been investigated through psychometric subjective experiment, where participants have evaluated the overall quality of stereoscopic images with varying both presences of depth and compression levels. The results reveal that compression artifacts dominate the quality of experience compared to varying depth range.
Why HDR is Important for 3DTV Model Acquisition

Mechanisms for automatically acquiring high quality 3D content of both indoor and outdoor scenes are essential research topics within 3D Television (3DTV). The envisioned goal is that a photo-realistic 3D real-time rendering from the actual and potentially arbitrary viewpoint of the beholder who is watching 3DTV becomes possible. Such scenes include movie sets in studios, e.g., for talk shows, TV series and blockbuster movies, but also outdoor scenes, e.g., buildings in a neighborhood for a car chase or cultural heritage sites for a documentary. The goal of 3D model acquisition is to provide the 3D background models where potential 3D actors can be embedded. Although model acquisition platforms have become available, the dynamic range of the used cameras is too limited to fully cover real world environments. We present two multi-sensor systems for 3D model acquisition, demonstrate the need for high dynamic range (HDR) capable acquisition platforms and propose a system that performs HDR computation to produce 3D models with tone mapped HDR information. Combining depth and HDR color information, a Markov Random Field based technique is used to get best out of both worlds - the high spatial resolution of the tonemapped HDR image with the depth field of a time-of-fiight camera.
Wavelet domain Wiener filtering for ECG denoising using improved signal estimate

A new two-stage algorithm for electrocardiographic (EGG) signal denoising has been proposed. It combines wavelet shrinkage with Wiener filtering in the translation-invariant wavelet domain. A time-frequency dependent thresholding has been proposed and grounded for obtaining a more adequate signal estimate in the first stage of the algorithm. It is related to ECG signal morphology and hence outperforms other thresholding approaches in this area. The experiments carried out on pathological and normal ECGs have shown better algorithm capabilities in comparison with other thresholding algorithms while suppressing parasite electromyographic (EMG) signals (the noise) and preserving diagnostically important ECG signal features.
Shearlet-domain light field reconstruction for holographic stereogram generation

Holographic stereograms (HSs) constitute one of the most widely used types of computer-generated holograms. The scene information required to calculate the HSs can be acquired by conventional digital cameras. It is, however, usually required that the scene should be captured from dense set of view points. Therefore, relieving this requirement is critical in the sense of easing the capture process. In this paper, in the capture stage of holographic stereograms, we employ our previously presented light field reconstruction algorithm , where we utilize sparse representation of light fields in the shearlet domain and reconstruct dense light fields from their highly under-sampled versions. The simulation results demonstrate that we can relieve the dense view sampling requirement of HSs, e.g. by as high as 8 × 8 sub-sampling factor, and still keep the perceived image quality of holographic reconstructions at satisfactory levels. This enables, for example, replacing the scanning camera setups with the more convenient multi-camera arrangements.
Edge-preserving image resizing using modified B-splines

An edge-preserving method for image resizing (decimation and interpolation) is proposed. The decimation is considered as an orthogonal projection with respect to the chosen interpolation basis. The latter one is formed in a spline-like manner as a linear combination of B-splines of different degrees. This combination is optimized in such a way that the small image details are preserved. Considering the strongest edges as step edges, a segmentation procedure preceding the decimation is proposed. It leads to resized images with clearly outlined borders.