nils-herrmann/clean_scirepeval huggingface dataset:
A region-specific QIM-based watermarking scheme for digital images

Angle Quantization Index Modulation (AQIM) is a watermarking technique that achieves provably good capacity-distortion-robustness performance. The scheme embeds each bit of a watermark message on an image by quantizing the angle formed by a vector of pixels or frequency coefficients from the host image with the origin of a hyperspherical coordinate system. While it has been demonstrated that AQIM is insensitive to intensity scaling attacks, the quantization step employed throughout the embedding process is set to a constant value regardless of the nature of the image. Because of this, the perceptual quality of the watermarked image cannot be regulated. In this paper, we propose a straightforward yet powerful AQIM-based watermarking scheme that considers the statistical behavior of the region where a message bit is to be embedded before settling on the size of the quantization step. Experimental results show that, for the same watermark capacity and image fidelity parameters, our proposed region-specific scheme exhibits a lower bit error rate than the regular AQIM approach.
An Efficient Multiple Description Coding Scheme for the Scalable Extension of H.264/AVC (SVC)

The demand for efficient scalable video codecs has constantly been on the rise in response to the increase in the variety of services and QoS requirements in multimedia networks. Existing standardization efforts, such as the scalable video coding extension of the H.264/AVC standard, do not offer efficient error resilient protection for all the different levels of video enhancement. We developed a multiple description scalable video coding technique that offers complementary and independently decodable descriptions, offering acceptable video quality even if only one of them is successfully received. Performance evaluations show that our scheme delivers an average improvement of 5 dB for single channel decoding and an improvement of 2 dB on average for packet loss simulations when compared with the UXP protected SD-SVC and the multiple-description motion compensated temporal filtering (MD-MCTF) scheme at comparable redundancy levels
Offline and online identification of hidden semi-Markov models

We present a new signal model for hidden semi-Markov models (HSMMs). Instead of constant transition probabilities used in existing models, we use state-duration-dependant transition probabilities. We show that our modeling approach leads to easy and efficient implementation of parameter identification algorithms. Then, we present a variant of the EM algorithm and an adaptive algorithm for parameter identification of HSMMs in the offline and online cases, respectively.
Using temporal correlation for fast and highdetailed video tone mapping

Tone Mapping Operators (TMOs) approximate the appearance of High-Dynamic-Range (HDR) content in standard displays. The few available video TMOs are computationally complex versions of existing schemes developed for still images. We introduce a fast method for video tone mapping that takes advantage of the strong temporal correlation that is usually found in video sequences. Each frame is divided into several blocks and we employ a motion estimation scheme that searches for similar blocks in a previously tone-mapped reference frame. The bilateral filter TMO is employed for the reference frames, but any other TMO can be used with our scheme. Experiments show that high-detailed tone-mapped content can be created without the need of employing a complex TMO on every frame.
Real-time DVB-MHP to Blu-ray system information transcoding

The demand for interactive TV services is rapidly increasing. Most of the interactive TV systems are based on the DVB-MHP (digital video broadcast - multimedia home platform) format. Given the unprecedented success of DVD technology and its already established installed base, it is definitely in the interest of manufactures and end-users to be able to play back DVB-MHP iTV content using a Blu-ray player. This study addresses how such programs could be played by the Blu-ray system in real-time. One of the main challenges in realizing this compatibility is the conversion of the "system information " data. These data carry the information about the broadcasting programs and services. This paper first analyzes the differences in system information between the two standards, DVB-MHP and Blu-ray; mainly the information each standard requires, where this information is stored, and how it is organized. We then propose methods to transcode this information in real-time. To derive the data required to generate the Blu-ray system information from a transport stream, we propose a data retrieval scheme that avoids fully demultiplexing a transport stream. To extract the needed information from the DVB-MHP video stream, we propose an efficient search algorithm. Finally, an improved structure that transcodes the incoming system information is developed. This transcoder only transcodes the updated versions of the system information and at the same time keeps the rate at which this information is transmitted to the Blu-ray system the same as that in DVB-MHP.
H.264-Based Compression of Bayer Pattern Video Sequences

Most consumer digital cameras use a single light sensor which captures color information using a color filter array (CFA). This produces a mosaic image, where each pixel location contains a sample of only one of three colors, either red, green or blue. The two missing colors at each pixel location must be interpolated from the surrounding samples in a process called demosaicking. The conventional approach to compressing video captured with these devices is to first perform demosaicking and then compress the resulting full-color video using standard methods. In this paper two methods for compressing CFA video prior to demosaicking are proposed. In our first method, the CFA video is directly compressed with the H.264 video coding standard in 4:2:2 sampling mode. Our second method uses a modified version of H.264, where motion compensation is altered to take advantage of the properties of CFA data. Simulations show both proposed methods give better compression efficiency than the demosaick-first approach at high bit rates, and thus are suitable for applications, such as digital camcorders, where high quality video is required.
Correction of Clipped Pixels in Color Images

Conventional images store a very limited dynamic range of brightness. The true luma in the bright area of such images is often lost due to clipping. When clipping changes the R, G, B color ratios of a pixel, color distortion also occurs. In this paper, we propose an algorithm to enhance both the luma and chroma of the clipped pixels. Our method is based on the strong chroma spatial correlation between clipped pixels and their surrounding unclipped area. After identifying the clipped areas in the image, we partition the clipped areas into regions with similar chroma, and estimate the chroma of each clipped region based on the chroma of its surrounding unclipped region. We correct the clipped R, G, or B color channels based on the estimated chroma and the unclipped color channel(s) of the current pixel. The last step involves smoothing of the boundaries between regions of different clipping scenarios. Both objective and subjective experimental results show that our algorithm is very effective in restoring the color of clipped pixels.
Fair scheduling in multirate wireless access networks

Wireless access networks such as IEEE 802.16 employ a multi-rate physical layer. Such physical layer designs rely on a user-defined link adaptation mechanism that changes the coding and modulation schemes, thus the transmission rate, in order to maintain link reliability at a desired level under different channel conditions. The multirate operation has a significant effect on the fairness of the services provided in the Medium Access Control (MAC) layer. In this paper, we present methods and algorithms for fair scheduling in such multirate wireless networks. We define fairness in terms of temporal or throughput fair services, and present different methods for fair service provisioning. For this purpose, we first discuss the concepts behind fair scheduling in variable bitrate networks, and then examine a few specific algorithms. We analyze the performance of these algorithms using simulation experiments.
Saturated-pixel enhancement for color images

We propose an algorithm to correct both luma and chroma of the saturated pixels in an overexposed image. Our method is based on the strong chroma spatial correlation between saturated pixels and their surrounding unsaturated area. We first identify the saturated areas in the image. Then, we partition these areas into regions with similar chroma, and estimate the chroma of each saturated region based on the chroma of its surrounding unsaturated region. Next, we correct the saturated R, G, or B color channels according to the estimated chroma and the unsaturated color channel(s) of the pixel. The last step involves smoothing of the boundaries between regions of different saturation scenarios. Both objective and subjective experimental results show that our algorithm is very effective in restoring the color of saturated pixels.
Optimizing a Tone Curve for Backward-Compatible High Dynamic Range Image and Video Compression

For backward compatible high dynamic range (HDR) video compression, the HDR sequence is reconstructed by inverse tone-mapping a compressed low dynamic range (LDR) version of the original HDR content. In this paper, we show that the appropriate choice of a tone-mapping operator (TMO) can significantly improve the reconstructed HDR quality. We develop a statistical model that approximates the distortion resulting from the combined processes of tone-mapping and compression. Using this model, we formulate a numerical optimization problem to find the tone-curve that minimizes the expected mean square error (MSE) in the reconstructed HDR sequence. We also develop a simplified model that reduces the computational complexity of the optimization problem to a closed-form solution. Performance evaluations show that the proposed methods provide superior performance in terms of HDR MSE and SSIM compared to existing tone-mapping schemes. It is also shown that the LDR image quality resulting from the proposed methods matches that produced by perceptually-based TMOs.
Combining bitstream switching and FGS for H.264 scalable video transmission over varying bandwidth networks

A novel system combining the FGS scalability with stream switching based on H.264's SP frame concept is introduced. For high bandwidth variations, our proposed system switches from a low-quality stream to a higher-quality stream whereas low bandwidth variations are accommodated by using only the corresponding FGS enhancement layer. Experimental results show that our proposed system outperforms FGS by 2.9 dB and the H.264 based stream switching approach by 1.5 dB on average.
Contrast effect on 3D and 2D video perception

There are many factors and parameters that have an effect on the perceptual quality of 2D and 3D media. This paper investigates how the contrast affects 3D and 2D perceptions. We implemented the double stimulus continuous quality scale method to conduct subjective tests that evaluate the perceptual quality of experience of 3D video and its 2D counterpart at different contrast levels between the object of interest and the background. Our test set-up guarantees that the results are independent of the brightness reduction caused by a specific 3D viewing/displaying technology. Statistical analysis shows that the effect of contrast on the perceptual quality of 2D and 3D videos is similar.
A Random Forests-based approach for estimating depth of human body gestures using a single video camera

An efficient Random Forests (RF)-based method for estimating the depth of human-body gestures in real-time using a single video camera is proposed. The potential application of the proposed method is in computer video games that include a 3D gesture interaction system, where human-body movements are translated to computer commands and interact directly with virtual content. The main advantage of our approach is its simplicity and cost effectiveness, since it eliminates the need for designing and implementing depth sensing cameras or 3D video cameras on computers. Performance evaluations show that our approach results in estimating very realistic depth of human-body gestures on real time basis.
Guidelines for capturing high quality stereoscopic content based on a systematic subjective evaluation

Although 3D TVs have already been introduced to the consumer market, the availability of stereoscopic (3D) content remains a serious challenge. Another challenge is that while some manufacturers are introducing 3D cameras and Hollywood is using proprietary solutions, there are no guidelines for consistently capturing high quality stereoscopic content. In this paper, we present a comprehensive stereoscopic image database with content captured at various distances from the camera lenses. We conducted subjective tests to assess the perceived 3D quality of these images which were shown on displays of different sizes. Finally, we provide guidelines of acquisition distances between the cameras and the real scene.
An improved Bayesian algorithm for color image desaturation

Current digital imaging systems are unable to capture the entire dynamic range of the visible luminance, causing saturation in the very bright parts of a scene. Color distortion occurs when the amounts of saturation are different in the red (R), green (G), and blue (B) color channels. A Bayesian algorithm was developed in the past to correct the saturated pixels in raw images. For each image, it estimates the distributions of the R, G, and B color channels based on the unsaturated pixels, and then corrects the saturated pixels based on this prior distribution. In this paper, we improve this Bayesian algorithm by incorporating spatial information in the correction process. We utilize the strong spatial correlation of images as well as the correlation between the R, G, and B channels of each individual pixel to estimate the prior distributions of the R, G, and B color channels. The prior distribution of each saturated region is modeled individually based on its surrounding region, which is determined by morphological dilation. Experimental results show that our modified algorithm greatly outperforms the original Bayesian algorithm for fixing saturated pixels in color images.
Tone mapping for video gaming applications

Due to the increasing interest in physical-based rendering in High Dynamic Range (HDR) in game development and the lack of commercial HDR displays, tone mapping the HDR game content to match the capabilities of Standard Dynamic Range (SDR) displays is currently a topic of high importance. In this paper, we propose a global Tone-Mapping Operator (TMO) for video gaming applications which takes advantage of the unique characteristics of the rendered HDR content to reproduce a tone-mapped scene that best matches the appearance of the original HDR scene in terms of preserved global contrast and texture details. This results in a more appealing game and increases players' quality of experience.
Computationally efficient tone-mapping of high-bit-depth video in the YCbCr domain

High dynamic range (HDR) video content is able to provide superior picture quality. This is because the representation of HDR signals requires more bits than the 8-bit low dynamic range (LDR) video. Tone-mapping is the process that converts HDR to LDR signals. Most tone-mapping methods are derived only for the luminance component. This mapping function is then used in each of the R, G and B components to generate the LDR color image. This color tone mapping correction approach, however, cannot be directly applied to most videos since they are usually encoded in the YCbCr color space. This paper addresses this problem and proposes a tone-mapping method that is applied directly on the YCbCr signals. Experimental results show that the Cb and the Cr signals generated by our method are almost identical to those produced with the conventional pipeline up to round-off errors, with average PSNR at about 55 dB and average SSIM at 0.991. By avoiding all the round-off errors introduced in the conventional method, our approach provides a more accurate LDR picture. Moreover, the proposed solution has significantly lower complexity because it bypasses the processes such as color space transformation and up-sampling which are required by the conventional method.
Effect of eye dominance on the perception of stereoscopic 3D video

Asymmetric schemes have widespread applications in the 3D video transmission pipeline. The significance of eye dominance becomes a concern when designing such schemes. In this paper, in order to investigate the effect of eye dominance on the perceptual 3D video quality, a database of representative asymmetric stereoscopic sequences is prepared and the overall 3D quality of these sequences is evaluated through subjective experiments. Experiment results showed that viewers find an asymmetric video more pleasant when the view with higher quality is projected to their dominant eye. Moreover, the eye dominance changes the mean opinion quality score by 16 % at most, a result caused by slight asymmetric video compression. For all other representative types of asymmetry, the statistical difference is much lower and in some cases even negligible.
A digital video system for multi-program broadcasting

We developed an efficient digital video broadcasting system suitable for multi-program applications. This system uses a joint bit-rate approach to significantly increase the number of compressed video streams transmitted in one channel. Compared to CBR implementations, our approach improves the bandwidth allocation by an average of 112%. As a result, for the same picture quality, our system can free a large number of transponders, which in turn can be used to carry real-time broadcasting.
A noise resistant synchronization scheme for HDTV images

A method that increases the error resistance of the HDTV system and offers graceful picture degradation in the presence of bit errors, is presented. Due to the nature of the presently proposed compression schemes for HDTV systems, an error in a data bit does not only affect the block the bit belongs to, but unfortunately the effects of this error may perpetuate to the following blocks. This is because a bit error may cause loss of synchronization between the data bits and the picture blocks they represent. Our method restricts the effects of a bit error to a picture block whose size is significantly smaller than those used by the HDTV systems. We achieve synchronization by transmitting a header-word for each such synchronization block. Each header-word contains the number of data bits representing the compressed block. This header-word is protected by two levels of FEC code. To decrease the number of extra bits needed by the header-words, two different synchronization block sizes are used, a relatively small block size for the reference frames and a larger size for the inter-frames. The resulting method improves the quality of the picture in the presence of errors and defers the SNR at which the HDTV picture suddenly deteriorates by 2.5 to 3 dB. It also allows operation at higher order modulation transmission schemes, e.g., 32-QAM instead of 16-QAM, without the requirement of increased signal power.
Random Forests Based View Generation for Multiview TV

The appearance of multiview display systems in the consumer market is not far from reality. With technical knowledge in this field constantly improving, production of multiview content is the only other key factor that will determine the successful adoption of this technology. Multiview content can be generated from two or three views and their associated depth maps. Estimating a high quality depth map is challenging. Moreover transmission of depth map information requires extra bandwidth. In this study, we propose an effective algorithm, which utilizes a 3D visual attention model, multiple monocular depth cues and a fraction of depth information for estimating the whole depth map of the scene using the Random Forests (RF) machine learning algorithm. Having the estimated depth maps and stereo videos, other views may be synthesized. Performance evaluations have shown that the proposed method estimates high quality depth maps for stereo sequences from limited depth information. Implementation of our proposed technique in the future multiview pipeline eliminates the need for estimating and transmitting the whole depth map for all the views, producing high quality multiview content while reducing the required bandwidth.
Visual saliency aided High Dynamic Range (HDR) video quality metrics

As High Dynamic Range (HDR) video is emerging as the next revolution in digital entertainment, finding effective ways for measuring its visual quality is of paramount importance. In this paper, we utilize the saliency information derived from an HDR Visual Attention Model (VAM), called LBVS-HDR, for assessing the quality of HDR video content. To this end, this saliency information is incorporated into existing state-of-the-art HDR quality metrics such as the HDR-VDP-2, deltaE2000, mPSNR, and tPSNR as well as the Standard Dynamic Range (SDR) benchmark quality metric, PSNR. The Visual Information Fidelity (VIF) index is also included in our comparisons, as it is reported to perform well for HDR content. Comparing the results of the VAM-aided quality metrics with those of the original ones, we verified that, in general, using saliency prediction for HDR quality assessment improves the performance of all the existing quality metrics. We also observed that the VIF index achieves the highest correlation between the objective and subjective test results.
Lossless Compression of 4D Medical Images using H.264/AVC

Four dimensional (4D) medical data are sequences of volumetric images captured in time. These data sets are typically very large in size and demand a great amount of resources for storage and transmission. In this paper, we present a lossless compression technique for 4D medical images which is based on the H.264/AVC video coding standard. Our lossless compression technique efficiently exploits spatial and temporal redundancies between 2D image slices and 3D images in 4D medical images and eliminates any concerns regarding the effects of compression on image quality for diagnostic purposes. Performance evaluations have shown that the proposed compression technique outperforms current 4D compression methods by 70%
Color image desaturation using sparse reconstruction

In this paper, we propose an algorithm to estimate the true values of saturated pixels in color images. Pixel saturation occurs when at least one color channel is clipped at some value below the full dynamic range of the scene, resulting in a loss in image fidelity. The proposed algorithm is based on the assumptions that images are nearly sparse in an appropriate transform domain, and that saturated pixels can be inferred from the structure of non-saturated neighboring pixels. Consequently, we use a hierarchical windowing algorithm which selects image regions containing relatively few saturated pixels for processing. Starting with small sized regions, and progressively increasing the size, we solve a sparsity promoting constrained ℓ1 minimization problem for each selected region to recover the saturated pixels. Moreover, we provide simulation results to show the effectiveness of our algorithm.