nils-herrmann/clean_scirepeval huggingface dataset:
Efficient 4D motion compensated lossless compression of dynamic volumetric medical image data

Dynamic volumetric (four dimensional- 4D) medical images are typically huge in file size and require a vast amount of resources for storage and transmission purposes. In this paper, we propose an efficient lossless compression method for 4D medical images that is based on a multi-frame motion compensation process employing a 4D search, variable block- sizes and bi-directional prediction. Data redundancies are reduced by recursively applying multi-frame motion compensation in the spatial and temporal dimensions. The proposed method also uses a novel differential coding algorithm to reduce redundancies in motion vectors and a new context-based adaptive binary arithmetic coder (CABAC) for compression of the residual data. Performance evaluations on real medical images of varying modality resulted in lossless compression ratios of up to 16:1.
Adaptive optimization of non-constant luminance to constant luminance for HDR video distribution

Traditional pixel representations decompose luma and chroma information for improved compression efficiency. One widely-used example is the Y'CBCR color pixel representation which is mainly used in image and video compression. Two methods exist for converting RGB pixel representation to Y'CBCR: Non-Constant Luminance (NCL) and Constant Luminance (CL). CL equations are derived from the weighted combination of the targeted gamut color primaries in the light linear domain. NCL method applies the same equations on perceptually encoded values, thus leading to reduced compression efficiency and lower color quality compared to those of CL. However, given the increased implementation cost of CL, broadcasting companies and television manufacturers choose to use NCL. In this work, our motivation is to derive new equations that take advantages of the CL method's efficiency without increasing hardware complexity for High Dynamic Range video distribution. Our proposed method is designed to be content adaptive. Results indicate that improved color quality can be achieved in terms of DE100 metric for sequences with one prominent primaries (Red, Green, or Blue) when compared with the NCL approach.
Extremely fast selective enhancement method for fine granular scalable enabled H.264 video

A novel method, that selectively enhances the visually important regions in scalable H.264 video encoding, is proposed. The proposed method is extremely fast and is designed to be used in real-time video communications systems. The method is based on fine granular scalability (FGS). FGS provides a framework to adapt to variations in the channel bandwidth, and it was recently standardized in the streaming video profile of MPEG-4. FGS also provides to the encoder the ability to selectively enhance the regions that are visually important, increasing the subjective video quality. In this paper we use the emerging video coding standard, H.264, for encoding the base layer, as opposed to MPEG-4. H.264 has several key differences with its predecessor standards, one of them being the new inter coded macroblock types. It was observed that specific macroblock types indicate visually important regions. In our proposed method, the macroblock (MB) type information along with motion vector (MV) data are used to extract features such as motion activity and camera motion. These features are used for defining the regions to be enhanced. Since, all of the operations are taking place on a block-by-block basis, the method presented here has very low computational complexity and suitable for real-time video communication systems. Experimental results show that subjective quality of the video sequence is significantly improved using our method.
A Fast Demosaicking Method Directly Producing YCbCr 4:2:0 Output

Consumer digital cameras usually use a single light sensor together with a color filter array (CFA) for capturing color images. This results in a mosaic image being captured, where only one color sample (red, green or blue) is obtained at each pixel location. Demosaicking is the process of interpolating the two missing color samples at each location to generate a full color image. Virtually all current demosaicking methods produce an RGB output image. If the image is to be compressed afterwards, it will typically be converted from RGB to YCbCr 4:2:0 formats. In this paper we propose a new demosaicking method that directly produces an YCbCr 4:2:0 images, so the output can be directly compressed. Simulation results show that the proposed method provides higher image quality than fast RGB based demosaicking methods and has lower computational complexity1.
Channel Adaptive Multi-User Scalable Video Streaming with Unequal Erasure Protection

In this paper, we propose a solution to the problem of streaming multiple video sequences in a capacity constrained, error-prone network. This scenario arises in situations such as multiple mobile computers accessing streamed video through a single access point, or multiple cell phone users serviced by a single base-station. Our approach constitutes a rate-constrained distortion-minimized streaming scheme to allocate the appropriate rate for each video stream that achieves minimal distortion without violating the capacity constraint. Moreover, we developed an unequal erasure protection (UXP) scheme that minimizes the protected bitstream rate and the expected packet loss probability for each video frame. Performance evaluations show that this approach delivers an improved decoded video quality and fairer rate-allocation when compared with standard UXP and rate- allocation schemes, specifically in limited capacity and congested channels.
A Video Watermarking Scheme Based on the Dual-Tree Complex Wavelet Transform

A watermarking scheme that discourages theater camcorder piracy through the enforcement of playback control is presented. In this method, the video is watermarked so that its display is not permitted if a compliant video player detects the watermark. A watermark that is robust to geometric distortions (rotation, scaling, cropping) and lossy compression is required in order to block access to media content that has been re-recorded with a camera inside a movie theater. We introduce a new video watermarking algorithm for playback control that takes advantage of the properties of the dual-tree complex wavelet transform. This transform offers the advantages of the regular and the complex wavelets (perfect reconstruction, shift invariance, and good directional selectivity). Our method relies on these characteristics to create a watermark that is robust to geometric distortions and lossy compression. The proposed scheme is simple to implement and outperforms comparable methods when tested against geometric distortions.
Data transmission schemes for DVD-like interactive TV

Current interactive services for digital TV are limited. They basically display a Web page alongside the TV program, which enhances the viewer's experience by providing extra information about the TV program. We define new interactive services for digital TV, which provide DVD-like interactivity to TV viewers. These services enable viewers to control the content and final presentation of a TV program. Some of the attractive applications of our services include parental management, multilingual audio, multiangle video, video in video, etc. The challenge in implementing these services is in transmitting an extra audio or video stream (called incidental) along with the main streams of the TV program. In the first part of this paper, we present a framework for adding the incidental streams to the original transmission stream without increasing the required bandwidth, degrading the picture quality of the main streams, or violating the compatibility of the transmitted stream with standard TV receivers. In the second part of this paper, we explore the two basic mechanisms of the presented framework: traffic characterization and admission control. We present methods for implementing these mechanisms. Using our methods, one can determine whether a TV transmission network has the capability of sending an incidental stream or not. Simulations were conducted to test the validity of our method. The results verify that our method successfully transmits the incidental streams without any discrepancy and without affecting the quality of the main streams
Learning Multilevel Dictionaries for Compressed Sensing Using Discriminative Clustering

The performance of sparse recovery using compressed measurements improves when dictionaries learned from training data are used in place of predefined dictionaries. In this paper, we propose to learn incoherent multilevel dictionaries using discriminative clustering in each level. To this end, we present the discriminative K-lines clustering that iterates between identifying the cluster centers and computing the discriminant directions. A scheme for computing representations using the proposed dictionary is also developed. Simulation results for compressed sensing using standard images demonstrate that incorporating incoherence in the dictionary results in improved recovery performance. Furthermore, we implement the proposed algorithms as part of a sparse representations toolbox for the J-DSP software package.
Human action recognition using meta learning for RGB and depth information

In this paper, we propose an efficient human action recognition technique, which utilizes Depth and RGB information of the scene. Our proposed technique, first builds a pair of classifiers based on RGB and depth information to independently predict the actions within a scene. Then, the obtained results from these classifiers are combined to achieve high accuracies in human action recognition. Our experimental results show that using an efficient amalgamation of depth-based and RGB-based classifiers improves human action recognition in smart home applications.
Real-time joint rate and protection allocation for multi-user scalable video streaming

In this paper, we present a real-time joint bit-rate and error protection allocation scheme for multiple scalable video streams sharing a single downlink channel. High speed downlink packet access (HSDPA) systems allow for multiple live video streams to share a common downlink channel among multiple mobile users. However, the unreliable nature of the wireless link results in packet losses and fluctuations in the available channel capacity. This calls for flexible error protection and rate control strategies implemented at the video encoders that can respond to the variation in channel conditions. In this paper, we formulate a global optimization problem, which is solved at every frame transmission instant and minimizes the expected sum of the video frame distortions of all users by adjusting the encoding quality at the base- and enhancement-layers as well as the application layer error protection overhead used to combat packet losses. We consider frame-level unequal erasure protection (UXP) as the application layer forward error correction scheme. Performance evaluations show that compared with existing schemes our proposed scheme delivers far superior decoded video quality averaging 1.2 dB in PSNR.
Optimizing Non Constant Luminance into Constant Luminance for High Dynamic Range Video Distribution

To improve compression efficiency, pixels are traditionally represented using a luma and two chroma values. Such a representation aims at separating light from color information. Two methods are usually considered for computing luma values: Non-Constant Luminance (NCL) and Constant Luminance (CL). CL equations have been derived from the luminous efficacy of the used gamut color primaries in the light linear domain. NCL applies the same equations but on perceptually encoded values, thus resulting in lower compression efficiency and hue shifts. However, given the higher hardware complexity for implementing CL, the common operational practice in legacy television distribution is to use NCL. In this paper, our motivation is to derive a new set of equations that provides the compression benefits of CL with the lower complexity of NCL for High Dynamic Range video distribution. Results show that the proposed method increases compression efficiency significantly over the NCL approach while maintaining NCL's cost complexity.
Subjective evaluation of tone-mapping methods on 3D images

High dynamic range (HDR) imaging provides superior picture quality to traditional 8 bit, low dynamic range (LDR), image representations. Capturing images/videos in HDR format can avoid problems with over and under exposures. Tone-mapping is a process that converts from HDR to LDR, so that HDR content can be shown on existing displays. Tone mapping has been extensively studied in the context of 2D images/video but not for 3D content. This paper addresses the problem of presenting 3D HDR content on stereoscopic LDR displays and presents a subjective psychophysical experiment that evaluates existing tone-mapping operators on 3D HDR images. The results show that 3D content derived using tone-mapping is much preferred to that is captured directly with a pair of LDR cameras. Global tone-mapping methods (which better preserve global contrast) are found to produce images with better 3D effect than local tone-mapping operators (which produce images with high amounts of detail/texture). Also, the brightness of the tone-mapped images is found to be highly collated with perceived 3D quality.
Automatic stereoscopic 3D video reframing

3D displays have various aspect ratios (e.g., 16:9, 4:3, and 3:2). Watching 3D videos with the wrong aspect ratio decreases the quality of the viewing experience. We have developed a smart reframing solution that uses a visual attention model for stereoscopic 3D video to identify the prominent visual regions of every stereoscopic frame. Our method uses several saliency indicators such as depth, edges, brightness, color, and movement. Additionally, our method provides a dynamic cropping window that slides smoothly from frame to frame.
A wavelet-based intra-prediction lossless image compression scheme

We propose a wavelet-based intra-prediction image coding scheme that is very efficient for lossless compression. This scheme takes advantage of JPEG-2000's wavelet decomposition and H.264's intra-prediction capability to compress still images. The compression performance is analyzed, and the results demonstrate that our method outperforms H.264 intra-mode coding by about 7% and JPEG-2000 by around 15% for the lossless case.
MPEG-2 video coding with image partitioning

In this paper we present an original motion compensation strategy based on frame partitioning. The proposed method uses different temporal resolutions within a frame to improve compression. We present a new bit allocation and rate control algorithm complementing our motion compensation technique. This unique approach to bit allocation ensures the consistency of quality throughout a single frame and a GOP. For the same picture quality, frame partitioning alone yields an additional increase of up to 20 percent or more of the encoding efficiency.
An improved error concealment algorithm for intra-frames in H.264/AVC

The highly error-prone nature of wireless environments and limited computational power of mobile devices necessitates the implementation of robust yet simple error concealment in H.264/AVC. We propose a new and effective error concealment algorithm for intra-coded frames that utilizes the temporal redundancy in a wireless video bitstream. The proposed concealment method supports both raster scan and FMO type slices. Performance evaluations show that our approach achieves significant improvement over existing methods in both PSNR and subjective picture quality.
A Service-Oriented Mobile Social Networking Platform for Disaster Situations

This paper proposes a novel service-oriented mobile social networking platform called MS2A for disaster situations. MS2A consists of two layers: service layer and application layer. The service layer is implemented based on the service-oriented architecture (SOA) to ease application developments. By extending and composing the web services at this layer, application developers can efficiently and flexibly develop different new functions or applications for mobile disaster rescue and recovery applications. The application layer is oriented to mobile users and it integrates with functions of mobile social networks. With dynamic and automatic service collaboration support, it enables people to easily collaborate and help each other through their mobile devices in disaster situations. The results of our experiments and demonstration examples given in the paper show the feasibility and desired functionality of MS2A for relieving disaster situations with mobile devices.
Efficient Lossless Compression of 4-D Medical Images Based on the Advanced Video Coding Scheme

This paper presents an efficient lossless compression method for 4-D medical images based on the advanced video coding scheme (H.264/AVC). The proposed method efficiently reduces data redundancies in all four dimensions by recursively applying multiframe motion compensation. Performance evaluations on real 4-D medical images of varying modalities including functional magnetic resonance show an improvement in compression efficiency of up to three times that of other state-of-the-art compression methods such as 3D-JPEG2000.
Combined link adaptation and traffic control scheme for MGS H.264/AVC video transmission

In this paper, we propose a joint link-adaptation and traffic control algorithm that efficiently allocates network resources to support multiple scalable video users over a capacity constrained wireless channel. Multi-rate networks, such as IEEE 802.16 or IEEE 802.11 use a link adaptation mechanism in the physical layer (PHY) and adjust the coding and modulation schemes to maintain the reliability of transmission under varying channel conditions. We consider Medium Grain Scalable (MGS) H.264/AVC video and employ a traffic control module that selectively drops individual video packets based on the packet dependencies in MGS. We present a framework that jointly optimizes the operation of the link adaptation and packet drop modules to achieve the highest video quality, while satisfying bandwidth/capacity constraints. Performance evaluations show that our proposed framework results in significant gains over existing schemes in terms of average video PSNR that can reach 3dB in some cases for different channel SNRs and different bandwidth budgets.
A content adaptive complexity reduction scheme for HEVC-based 3D video coding

3D-HEVC is aiming at utilizing the advanced tools present in HEVC to efficiently code multiview video content. The computational complexity of this codec is significantly increased and is a challenge for real-time applications. In our study, we propose an adaptive early-termination inter and intra prediction mode search that reduces the 3D-HEVC coding complexity by utilizing the correlations between views, while maintaining the overall video quality.
Color correction of multiview video with average color as reference

When capturing multiview video, there can be significant variations in the color of views captured with different cameras. This negatively affects compression efficiency when multiview video is coded using inter-view prediction. In this paper we propose a method for correcting the color of multiview video sets as a preprocessing step to compression. Unlike previous work where one of the captured views is used as the color reference, we correct all views to match the average color of the set of views. Block based disparity estimation is used to find matching points between all views in the video set, and the average color is calculated for these matching points. Least squares regressions are used to find functions that will make each view match the average color. Experimental results show that the proposed method results in video sets that closely match in subjective color. Furthermore, when multiview video is compressed with JMVM, the proposed method increases compression efficiency by up to 1.0 dB compared to compressing the original uncorrected video.
A Framework of Cooperative Cell Caching for the Future Mobile Networks

The demand for rich multimedia services over mobile networks has been soaring at a tremendous pace over recent years. However, the wireless link capacity as well as the bandwidth of the radio access networks and the backhaul network cannot practically cope with the explosive growth in mobile traffic load. In this article, we mainly focus on a new novel framework of cooperative cell caching for future mobile cellular networks, where the base station of each cell can have certain capability of caching popular contents. Then we carry out necessary theoretical modeling-based analysis. We also propose to utilize prefix-tree aggregation to improve the caching performance among cells, and discuss potential deployment issues for caching in 5G mobile networks. Based on trace-driven simulations, we evaluate the performance of the proposed framework.
Perception-based Histogram Equalization for tone mapping applications

Due to the ever increasing commercial availability of High Dynamic Range (HDR) content and displays, backward compatibility of HDR content with Standard Dynamic Range displays is currently a topic of high importance. Over the years, a significant amount of Tone Mapping Operators (TMOs) have been proposed to adapt HDR content to the restricted capabilities of SDR displays. Among them, the Histogram Equalization (HE) is considered to provide good results for a wide set of images. However, the naïve application of HE results either in banding artifacts or noise amplification when the HDR image has large unified areas (i.e. sky). In order to differentiate relevant information from noise in a uniform background, or in dark areas, the authors proposed a ceiling function. Their method results in noise-free but dim images. In this paper we propose a novel ceiling function which is based on the Perceptual Quantizer (PQ) function. Our method uses as threshold the number of code-words that PQ assigns on a luminance range in the original HDR image and the corresponding number of code-words in the resulting SDR image. We limit the number of code-words on SDR to be equal or less than the HDR. The saved code-words during the ceiling operation are redistributed to increase the contrast as well as the brightness of the final image. Results shows that provided SDR images are noise-free and brighter than the one obtained with prior HE operators. Finally since the proposed method is a Global TMO, it is thereby of low complexity and suitable for real time applications.
Color Correction Preprocessing for Multiview Video Coding

In multiview video, a number of cameras capture the same scene from different viewpoints. There can be significant variations in the color of views captured with different cameras, which negatively affects performance when the videos are compressed with inter-view prediction. In this letter, a method is proposed for correcting the color of multiview video sets as a preprocessing step to compression. Unlike previous work, where one of the captured views is used as the color reference, we correct all views to match the average color of the set of views. Block-based disparity estimation is used to find matching points between all views in the video set, and the average color is calculated for these matching points. A least-squares regression is performed for each view to find a function that will make the view most closely match the average color. Experimental results show that when multiview video is compressed with joint multiview video model, the proposed method increases compression efficiency by up to 1.0 dB in luma peak signal-to-noise ratio (PSNR) compared to compressing the original uncorrected video.