nils-herrmann/clean_scirepeval huggingface dataset:
A progressive transmission image coder using linear phase uniform filterbanks as block transforms

This paper presents a novel image coding scheme using M-channel linear phase perfect reconstruction filterbanks (LPPRFBs) in the embedded zerotree wavelet (EZW) framework introduced by Shapiro (1993). The innovation here is to replace the EZWs dyadic wavelet transform by M-channel uniform-band maximally decimated LPPRFBs, which offer finer frequency spectrum partitioning and higher energy compaction. The transform stage can now be implemented as a block transform which supports parallel processing and facilitates region-of-interest coding/decoding. For hardware implementation, the transform boasts efficient lattice structures, which employ a minimal number of delay elements and are robust under the quantization of lattice coefficients. The resulting compression algorithm also retains all the attractive properties of the EZW coder and its variations such as progressive image transmission, embedded quantization, exact bit rate control, and idempotency. Despite its simplicity, our new coder outperforms some of the best image coders published previously in the literature, for almost all test images (especially natural, hard-to-code ones) at almost all bit rates.
Fundus based eye tracker for optical coherence tomography

Current optical coherence tomography (OCT) relies on patient cooperation to maintain fixation. For patients with eye complications, it is extremely difficult to achieve fixation on the eye. Most eye trackers are external and track only the pupils. Such method is not useful for the OCT. The only existing fundus image based tracker is a hardware-based system that is composed of a confocal reflectometer, dither scanner, and tracking galvanometers. The integration of such hardware based system with the OCT is not as desirable nor as portable. Therefore, we want an eye tracking system that can be installed in the computer connected to the OCT. In this paper, a real time internal eye tracking software based system is proposed. By combining intensity based object tracking adaptive mean shift algorithm with Kalman filtering techniques together, a robust real time eye tracking algorithm is proposed. The system is robust in terms of its acceptance to low resolution, coarsely quantized, or extremely noisy images and still able to produce desirable results with no pre-processing of images.
A block-based super-resolution for video sequences

An algorithm for video resolution enhancement is presented. The approach borrows from previous methods for still-image super- resolution, introducing modifications better suited for the characteristics specific to video domain problems. Each high-resolution (HR) frame is determined through a series of MMSE spatial interpolations based on the local features (statistics) of the frame. Cross-frame registration is estimated externally and the reconstruction algorithm does not limit the form of the motion model, unlike previous data-fusion/deconvolution approaches which have required motion models that do not alter the point-spread function (i.e., motion/blur commutability). This feature is made possible using a reverse motion model mapping the locations of desired HR pixels onto their corresponding locations in the observation frames. An ticipating the existence of registration error found in typical video sequences, the algorithm also provides an internal validation of the observation pixels, helping to reduce significant mis-registration artifacts. An arbitrary enhancement factor can be used, allowing an output at any desired resolution. Interpolation and deblurring are incorporated as a single MMSE filtering operation, providing a non-iterative one-step reconstruction process. Experimental results demonstrating the capabilities of the algorithm are made available.
On arbitrary-length, M-channel linear-phase FIR filter banks

This paper investigates the existence of a large subclass of M-channel linear-phase perfect-reconstruction FIR filter banks-systems with analysis and synthesis filters of length L/sub i/=K/sub i/M+/spl beta/, where /spl beta/ is an arbitrary integer, 0/spl les//spl beta/<M, and K/sub i/ is any positive integer. For this subclass of systems, and for any arbitrary channel M, we first derive the necessary conditions for the existence of linear-phase perfect-reconstruction filter banks. Next, we turn our attention to a large class of linear-phase paraunitary filter banks, those with even M and even /spl beta/, and develop a simple lattice structure for this case. Finally, several design examples are presented to confirm the validity of the theory.
Joint Defogging and Demosaicking

Image defogging is a technique used extensively for enhancing visual quality of images in bad weather conditions. Even though defogging algorithms have been well studied, defogging performance is degraded by demosaicking artifacts and sensor noise amplification in distant scenes. In order to improve the visual quality of restored images, we propose a novel approach to perform defogging and demosaicking simultaneously. We conclude that better defogging performance with fewer artifacts can be achieved when a defogging algorithm is combined with a demosaicking algorithm simultaneously. We also demonstrate that the proposed joint algorithm has the benefit of suppressing noise amplification in distant scenes. In addition, we validate our theoretical analysis and observations for both synthesized data sets with ground truth fog-free images and natural scene data sets captured in a raw format.
A Shift-Invariant Multiscale Multidirection Image Decomposition

This paper presents a shift-invariant complex directional pyramid transform constructed by a dual-tree pyramidal directional filter banks (DFB). The double filter bank framework consists of a shift-invariant Laplacian pyramid and a dual-tree DFB. The two binary tree structure for the (primal and dual) DFBs employed in the structure are identical except for the filter bank employed at the second level of the dual DFB, where special conditions on the phase of the filters are required. It is proven analytically and experimentally that each pair of corresponding directional filters produced by the primal and dual filter banks are symmetric and anti-symmetric, which can be interpreted as the real and imaginary parts of a complex filter. Therefore, the two subband coefficients can be viewed as the real and imaginary parts of a complex-valued subband image. It is proven that there is no aliasing in the decimated complex-valued signal, which implies that the system is shift-invariant in the energy sense. In addition, the proposed shift-invariant, multiscale, multidirectional image decomposition has two unique characteristics that other shift-invariant decompositions do not possess. First, the directional resolution of the image transform can be arbitrarily high. Secondly, the two-dimensional filter bank is implemented in a separable fashion, which makes the entire structure very computational efficient
Realistic Photonic Filter Design Based on Allpass Substructures With Waveguide Loss Compensation

We present a lowpass design algorithm targeted specifically for photonic implementation. Allpass filter based systems are ideal for photonic realizations because they can be naturally realized using a variety of nanoscale dielectric components. The allpass filters based lowpass system is a particularly noteworthy example of advanced usages of allpass sub-structures. While the structure is excellent for implementation using photonic components, practical considerations about its suboptimal performance are yet to be considered. Realistic optical filters are subject to the imperfections of photonic materials and limitations from current fabrication capability. The waveguide power loss is an unavoidable source of performance degradation that arises when realizing photonic filters. In this paper, we consider the derivation of allpass filters based lowpass structures that can minimize the loss effect. The proposed algorithm will enable the utilization of low cost photonic devices for stringent design requirements, and also improve the performance of high end photonic devices.
Multirate as a hardware paradigm

The architecture and circuit design are the two most effective means of reducing power in CMOS VLSI. Mathematical manipulations, based on applying ideas from multirate signal processing have been applied to create high performance, low power architectures. To illustrate this approach, two case studies are presented-one concerns the design of a fast Fourier transform (FFT) device, while the other one is concerned with the design of analog-to-digital converters.
Determination of receiver susceptibility to radio frequency interference from portable electronic devices

With the increasing pressures to allow wireless devices on aircraft the susceptibility of aircraft receivers to interference from portable electronic devices (PEDs) becomes an increasing concern. Many investigations were conducted in the past, with limited success, to quantify device emissions, path loss, and receiver interference susceptibility thresholds. This paper outlines the recent effort in determining the receiver susceptibility thresholds for ILS, VOR and GPS systems. The effort primarily consists of analysis of data available openly as reported in many RTCA and ICAO documents as well as manufacturers data on receiver sensitivity. Shortcomings with the susceptibility threshold data reported in the RTCA documents are presented, and an approach for an in-depth study is suggested. In addition, intermodulation products were observed and demonstrated in a laboratory experiment when multiple PEDs were in the proximity of each other. These intermodulation effects generate spurious frequencies that may fall within aircraft communication or navigation bands causing undesirable effects. Results from a preliminary analysis are presented that show possible harmful combinations of PEDs and the potentially affected aircraft bands.
A New Objective Quality Metric for Frame Interpolation Used in Video Compression

A new metric for assessing spatial quality of the temporally interpolated frames is proposed. It is designed to overcome disadvantages found in several widely used metrics for the frame interpolation application. The proposed metric quantifies the severities of several pronounced interpolation artifacts and combines them along with human visual factors to form a global (i.e. frame-wide) quality measurement. Also, the artifact amounts are used to determine additional quality impairment caused by locally aggregated distortion. Finally, these two measurements are combined into a single quality score. Subjective experiments show that the proposed metric significantly outperforms other commonly used metrics.
Distributed Shortcut Networks: Low-Latency Low-Degree Non-Random Topologies Targeting the Diameter and Cable Length Trade-Off

Low communication latency becomes a main concern in highly parallel computers and supercomputers that reach millions of processing cores. Random network topologies are better suited to achieve low average shortest path length and low diameter in terms of the hop counts between nodes. However, random topologies lead to two problems: (1) increased aggregate cable length on a machine room floor that would become dominant for communication latency in next-generation custom supercomputers, and (2) high routing complexity that typically requires a routing table at each node (e.g., topology-agnostic deadlock-free routing). In this context, we first propose low-degree non-random topologies that exploit the small-world effect, which has been well modeled by some random network models. Our main idea is to carefully design a set of various-length shortcuts that keep the diameter small while maintaining a short cable length for economical passive electric cables. We also propose custom routing that uses the regularity of the various-length shortcuts. Our experimental graph analyses show that our proposed topology has low diameter and low average shortest path length, which are considerably better than those of the counterpart 3-D torus and are near to those of a random topology with the same average degree. The proposed topology has average cable length drastically shorter than that of the counterpart random topology, which leads to low cost of interconnection networks. Our custom routing takes non-minimal paths to provide lower zero-load latency than the minimal custom routings on different counterpart topologies. Our discrete-event simulation results using SimGrid show that our proposed topology is suitable for applications that have irregular communication patterns or non-nearest neighbor collective communication patterns.
Eigenfilter approach for the design of allpass filters approximating a given phase response

We apply the eigenfilter method to design an allpass filter that approximates a given phase response in the least-squares (LS) sense. As it is not possible to express the exact LS phase error as a quadratic form suitable for eigenfilter formulation, alternative error measures that approximate the ideal LS error are proposed. For each of these new formulations, the allpass coefficients are obtained as the elements of the eigenvector corresponding to the minimum eigenvalue of a real, symmetric, and positive definite matrix. We propose a fast-converging iterative technique to approximate the ideal LS phase error solution. By employing an iterative weighting technique, the phase error can he made approximately equiripple. The design methods are illustrated with various practical examples and the results are compared to allpass filters designs reported in the literature.
Rate Control Scheme for Consistent Video Quality in Scalable Video Codec

Multimedia data delivered to mobile devices over wireless channels or the Internet are complicated by bandwidth fluctuation and the variety of mobile devices. Scalable video coding has been developed as an extension of H.264/AVC to solve this problem. Since scalable video codec provides various scalabilities to adapt the bitstream for the channel conditions and terminal types, scalable codec is one of the useful codecs for wired or wireless multimedia communication systems, such as IPTV and streaming services. In such scalable multimedia communication systems, video quality fluctuation degrades the visual perception significantly. It is important to efficiently use the target bits in order to maintain a consistent video quality or achieve a small distortion variation throughout the whole video sequence. The scheme proposed in this paper provides a useful function to control video quality in applications supporting scalability, whereas conventional schemes have been proposed to control video quality in the H.264 and MPEG-4 systems. The proposed algorithm decides the quantization parameter of the enhancement layer to maintain a consistent video quality throughout the entire sequence. The video quality of the enhancement layer is controlled based on a closed-form formula which utilizes the residual data and quantization error of the base layer. The simulation results show that the proposed algorithm controls the frame quality of the enhancement layer in a simple operation, where the parameter decision algorithm is applied to each frame.
Interpolated Mth band filters for image size conversion

Image/video size conversion at variable rates requires that a large set of interpolation filters should be stored in a table. We present the interpolated Mth band filters as the interpolation filters. The interpolated Mth band filters are obtained from the cubic spline interpolation of a prototype M/sub p/th band eigenfilter. The proposed filter can be calculated in real time, eliminating the need for a large on-chip memory. Scaled images using the proposed filters show superb image quality.
Linear phase FIR paraunitary filter banks and higher multiplicity wavelet given several analysis filters

The theory and design of paraunitary filter banks where several analysis filters are given is considered in this paper. Factorization based algorithm is derived for paraunitary completion problem with linear and nonlinear phase filters and arbitrary number of channels. A time domain algorithm is derived which formulates the problem in quadratic form for computational efficiency. Both algorithms are shown to completely characterize all embedding solutions. The existence of orthogonal wavelet with higher multiplicity and with arbitrary number of channels is considered and design example is presented.
Motion vector processing based on trajectory curve analysis for motion compensated frame interpolation

In this paper, we propose a novel motion vector processing approach based on the temporal analysis of motion vector reliability for motion-compensated frame interpolation. We first address the problems of conventional methods that find motion by minimizing the difference between the forward and backward predictions. The ghost artifacts can be reduced due to this procedure, but the resulting motion vectors may not represent the actual motion. Therefore, we propose analyzing the temporal variations of the bidirectional prediction difference along the motion trajectory to detect temporally unreliable motion vectors and further improve the accuracy of the bidirectional motion vector processing. Experimental results show that the proposed method can effectively detect unreliable motion vectors and outperforms other methods in terms of visual quality, and structure similarity.
3D Video Fingerprinting

Two new attacks on multiview videos in the view space is investigated, which is also applicable to stereo and free-view television. The first attack involves the generation of new views from different viewpoints. The second attack involves change in the region of focus (the display plane or the zero disparity plane) in the multiview images. A scale invariant feature descriptor (SIFT) based fingerprinting mechanism which can identify such attacks is developed. An online verification system matches the SIFT descriptors of the original video (stored at a central database) to that of the attacked video. Results show that the method can detect such attacks well, and is useful for copy detection on the internet.
Design of a photoconductive antenna with an angled DC bias connection on an extended hemispherical lens substrate

The input impedance and radiation characteristics of photoconductive antennas with different DC bias connection angles printed on an extended hemispherical lens made of high-dielectric-constant substrate was presented. Antennas with different bias connection angles exhibited different gain and radiation efficiency spectra for a specific lens geometry. The antennas with larger DC bias connection angles provided stable input impedance and improved antenna gain levels, particularly in the low-frequency region. This indicates that the DC bias connection angle has specific effects on the overall performance of the photoconductive antenna design.
Moving Object Detection With a Freely Moving Camera via Background Motion Subtraction

Detection of moving objects in a video captured by a freely moving camera is a challenging problem in computer vision. Most existing methods often assume that the background (BG) can be approximated by dominant single plane/multiple planes or impose significant geometric constraints on BG, or utilize a complex BG/foreground probabilistic model. Instead, we propose a computationally efficient algorithm that is able to detect moving objects accurately and robustly in a general 3D scene. This problem is formulated as a coarse-to-fine thresholding scheme on the particle trajectories in the video sequence. First, a coarse foreground (CFG) region is extracted by performing reduced singular value decomposition on multiple matrices that are built from bundles of particle trajectories. Next, the BG motion of pixels in the CFG region is reconstructed by a fast inpainting method. After subtracting the BG motion, the fine foreground is segmented out by an adaptive thresholding method that is capable of solving multiple-moving-objects scenarios. Finally, the detected foreground is further refined by the mean-shift segmentation method. Extensive simulations and a comparison with the state-of-the-art methods verify the effectiveness of the proposed method.
Frame rate up conversion of 3D video by motion and depth fusion

This paper presents a new frame-rate up conversion method for video plus depth representation. The proposed method improves the quality of video using additional depth information. The depth information is utilized in three ways to improve the accuracy of motion estimation. One usage is that depth frame is added in block matching criterion to estimate initial motion. Another usage is to detect object boundary region combining depth value variation and local depth distribution adjustment technique. Finally, motion vector field is refined adaptively by segmenting macroblocks into object regions. Any existing block-based motion-compensated frame interpolation methods may utilize our method to refine motion vector field by using depth frames. Experimental results verify that the proposed method outperforms the conventional motion-compensated frame interpolation algorithms, while preserving object structure.
A perceptual metric for blind measurement of blocking artifacts with applications in transform-block-based image and video coding

In this paper, we analyze the formation of blocking artifacts as a result of quantization of the discrete cosine transform (DCT) coefficients. These artifacts are known to be the dominant distortion of lossy block-based hybrid image and video coding schemes when operating at very low data rates. Our analysis is carried out based on the theory of edge detection and by means of a mathematical framework to model the properties of receptive fields, which are known to be the main mechanism for sensing intensity contrasts and edges. Based on our analysis we propose a metric to quantify the blocking artifact distortion. The proposed distortion metric considers the susceptibility of a region in a reconstructed (decoded) image to the formation of blocking artifacts via a probabilistic model, which quantifies the possibility of a detected edge to be a distortion.
Adaptive Image Denoising by Targeted Databases

We propose a data-dependent denoising procedure to restore noisy images. Different from existing denoising algorithms which search for patches from either the noisy image or a generic database, the new algorithm finds patches from a database that contains relevant patches. We formulate the denoising problem as an optimal filter design problem and make two contributions. First, we determine the basis function of the denoising filter by solving a group sparsity minimization problem. The optimization formulation generalizes existing denoising algorithms and offers systematic analysis of the performance. Improvement methods are proposed to enhance the patch search process. Second, we determine the spectral coefficients of the denoising filter by considering a localized Bayesian prior. The localized prior leverages the similarity of the targeted database, alleviates the intensive Bayesian computation, and links the new method to the classical linear minimum mean squared error estimation. We demonstrate applications of the proposed method in a variety of scenarios, including text images, multiview images, and face images. Experimental results show the superiority of the new algorithm over existing methods.