nils-herrmann/clean_scirepeval huggingface dataset:
Perceptual rate control for low-delay video communications

The existing rate control schemes in the literature evaluate their video quality performance in terms of traditional PSNR. Actually, this evaluation may not be good because this measurement is not the same as that judged by human. This work defines a perceptual quality measure based on the human vision system. The modified rate control includes the perceptual consideration. The results show that the perceptual rate control achieves average perceptual quality gain over TMN8.
An analysis on bitwise operations in the encrypted domain

When encrypted data need to be sent to an untrusted computer for processing, it is highly desirable to have a homomorphic cryptosystem that allows the untrusted computer to process the encrypted signals totally without decryption such that, when the encrypted domain result is decrypted, the decrypted value is the same as the equivalent plaintext domain operation. These operations range from basic arithmetic operations to complicated transformations. In this paper, we analyze the existence of equivalent operations in the encrypted domain for four of the common bitwise operations: OR, AND, NOR and NAND in plaintext domain. We will show that such equivalent operations should not exist. For otherwise, if such operations exist, the RSA cryptosystems can be broken by a low-complexity attack.
A blind watermarking technique in JPEG compressed domain

We propose a blind watermarking technique to embed a watermark in the JPEG compressed domain. Low frequency DCT coefficients are extracted to form an M-dimensional vector. Watermarking is achieved by modifying this vector in order to point to the centroid of a particular cell. This cell is determined according to the extracted vector, private keys and the watermark. A dual-key system is used to reduce the chance of the removal of watermark. An iterative approach is used to prevent the removal of the watermark by JPEG re-quantization. Experimental results show that the watermark can be detected when the watermarked image is further compressed using a larger scaling factor.
Objective speech measure for Chinese in wireless environment

The cellular phone is becoming an important means of mobile wireless communication, especially in metropolitan areas. One of the important operating considerations of the cellular phone service providers is the maintainence of the speech quality of the cellular phone network. Subjective evaluation by repeated listening tests at various sites within the coverage area is impractical due to its intrinsic laborious and expensive nature. As a result, it would be much desirable to have an automatic objective evaluation system which applies a good objective speech measure to estimate the statistical average of subjective opinions of the typical conversational speech sentences sent through the cellular network. While extensive work was done for objective speech measures for languages such as English, Japanese, French, and other western languages, little has been done for Chinese. In addition, little has been done to quantify speech quality in the wireless environment.
A Multihypothesis Motion-Compensated Temporal Filter for Video Denoising

Most existing filters for video denoising are spatio-temporal filters which operate on data over 3 dimensions. This paper presents a purely linear temporal filter with multihypothesis motion compensation (MC). Compared to the spatio-temporal filters, the proposed one needs much fewer inputs and much simpler operation. Experimental results show that just by involving 3 pixels, the proposed filter can achieve very good noise suppression performance. Moreover, as a purely temporal filter, it can well preserve spatial details and achieve satisfactory visual quality.
Anti-aliasing filter for subpixel down-sampling based on frequency analysis

Nowadays, digital pictures are usually captured at very high resolution ranged up to 12 mega-pixels. Limited by low-resolution display, we have to shrink the image. Signal processing theory tells us that optimal decimation requires low-pass filtering with a suitable cut-off frequency followed by down-sampling. In doing so, we need to remove lots of details. Subpixel-based down-sampling, taking advantage of the fact that each pixel on a color LCD is actually composed of individual red, green, and blue subpixel stripes, can provide apparent higher resolution. In this paper, we use frequency domain analysis to explain what happens in subpixel-based downsampling and why it is possible to achieve a higher apparent resolution. According to our frequency domain analysis and observation, the cut-off frequency of the low-pass filter for subpixel-based decimation can be effectively extended beyond the Nyquist frequency using a novel anti-aliasing filter. Experimental results verify that the proposed subpixel down-sampling scheme based on frequency analysis (SDSFA) can give superior results compared with existing pixel-based down-sampling methods.
An improved method for color images enhancement considering HVS

Viewing the image produces a subjective experience that corresponds with viewing the real scene. The preservation or enhancement of brightness, contrast, and color is very important for color image processing. While most previous algorithms are focusing on the luminance component, this paper presents an algorithm for color enhancement focusing on chromatic components in the compressed domain. On the basis of DC-T transform, the proposed algorithm provides different treatments on different image blocks considering the perceptual properties of Human Visual System (HVS). A simple method in reducing blocking artifacts, which is based on Weber-Fechner Law is introduced. This paper also compares the results of experiments and discusses the effects of different parameters. Experiments indicate that through choosing optimal parameter the algorithm performs better in color enhancement and blocking artifacts reduction compared to other compressed domain based approaches, such as alpha rooting.
Efficient intra-prediction mode selection for 4/spl times/4 blocks in H.264

In the upcoming H.264, intra-prediction for 4/spl times/4 and 16/spl times/16 blocks is used to compress I-frame. However, we need to choose one of the 9 prediction modes for each 4/spl times/4 block. The full search (FS) algorithm to select the mode is computationally expensive. In this paper, an efficient intra-prediction mode selection (EIPMS) method is proposed based on partial computation of the cost function, selective computation of highly probable modes, early termination, and variable threshold setting. The proposed EIPMS can reduce the complexity considerably while maintaining similar PSNR and bit rate.
Film grain noise removal and synthesis in video coding

In this paper, we propose new techniques for film grain noise removal and synthesis, which can be applied in video coding. Film grain noise is clearly noticeable in high-definition video, and should be preserved for the sake of natural look. However, film grain noise tends to reduce the coding efficiency because of its random nature. In our work, prior to video encoding, essential parameters of film grain noise are estimated and the noise is removed by temporal filtering; at the decoder size, film grain noise is modeled by an autoregressive (AR) model, synthesized using the estimated parameters, and added back to the decoded video. Simulation results show that the proposed algorithms can considerably reduce the bitrate and at the same time achieve good subjective quality.
Transform-Domain Adaptive Correlation Estimation (TRACE) for Wyner–Ziv Video Coding

Wyner-Ziv video coding (WZVC) is a newly emerged video coding scheme which compresses the input video frames with the side information (SI) frames only available at the decoder. WZVC exploits the statistics between the source frame and the SI frame at the decoder by utilizing their correlation information. This correlation information is important but also difficult to estimate due to the absence of the SI frame at the encoder, and the lack of the source frame at the decoder. In this paper, we focus on this problem and propose a novel transform-domain adaptive correlation estimation method called TRACE for WZVC. In TRACE, the correlation information is progressively learned during the decoding process of each frame. Within TRACE, we also propose a convex optimization based band-level correlation estimation method which is optimal in the sense of minimizing the theoretical bit rate. Experiments suggest that, when applied in motion compensated interpolation-based low complexity WZVC, TRACE yields competitive results against the state-of-the-art correlation estimation algorithms. More importantly, different from the existing coefficient-level correlation estimation algorithms, the proposed TRACE can be applied in many other WZVC schemes and can provide considerable gain over the popular band-level correlation estimation methods.
A highly data reusable and standard-compliant motion estimation hardware architecture

Motion Estimation (ME) is the most computationally intensive part in the whole video compression process. The ME algorithms can be divided into full search ME (FS) and fast ME (FME). The FS is not suitable for high definition (HD) frame size videos because its relevant high computation load and hard to deal with complex motions in limited search range. A lot of FME algorithms have been proposed which can significantly reduce the computation load compared to FS. Though many kinds of hardware implementations of ME have been proposed, almost all of them fail to consider about the motion vector field (MVF) coherence and rate-distortion (RD) cost which have significant impact to the coding efficiency. In this paper, we propose a hardware friendly ME algorithm and corresponding highly data reusable hardware architecture. Simulation results show that the proposed ME algorithm performs better RD performance than conventional FME algorithm. The proposed reconfigurable ME hardware is implemented in VHDL and mapped to a low cost Xilinx XC3S1500 FPGA. It works at 100MHz and is capable to process 1920 × 1080 of 30fps video format in real time and have very high data reuse ratio.
Error compensation and reliability based view synthesis

View synthesis offers a great flexibility in generating free viewpoint television (FTV) and 3D video (3DV). However, the depth-image-based view synthesis approach is very sensitive to errors in the camera parameters or poorly estimated depth maps (also called depth images). Because of these errors, three kinds of artifacts (blurring, contour, hole) are possibly introduced during the general synthesis process. Comparing to conventional methods which implement the view synthesis only in ideal case, in this paper, we propose to design an error compensation and reliability based view synthesis system where the potential errors are considered. The main contributions are highlighted as follows: Firstly, the camera parameter errors are compensated by a global homography transformation matrix. Secondly, the depth maps are classified into both reliable and unreliable regions and the reliability based weighting masks are built to blend synthesized images from two different views together. Finally, a reliability depth map based hole-filling technique is used to fill the existing holes. The experimental results demonstrate that these artifacts are efficiently reduced in the synthesized images.
Data hiding watermarking for halftone images

In many printer and publishing applications, it is desirable to embed data in halftone images. We proposed some novel data hiding methods for halftone images. For the situation in which only the halftone image is available, we propose data hiding smart pair toggling (DHSPT) to hide data by forced complementary toggling at pseudo-random locations within a halftone image. The complementary pixels are chosen to minimize the chance of forming visually undesirable clusters. Our experimental results suggest that DHSPT can hide a large amount of hidden data while maintaining good visual quality. For the situation in which the original multitone image is available and the halftoning method is error diffusion, we propose the modified data hiding error diffusion (MDHED) that integrates the data hiding operation into the error diffusion process. In MDHED, the error due to the data hiding is diffused effectively to both past and future pixels. Our experimental results suggest that MDHED can give better visual quality than DHSPT. Both DHSPT and MDHED are computationally inexpensive.
Advanced independent cascade model for YouTube content propagation in Facebook

Multimedia streaming service providers such as YouTube often need to design caching strategy based on predicted future media content propagation pattern. It is commonly observed that social network behavior tends to have great correlation with the content propagation pattern. In this paper, we propose an Advanced Independent Cascade Model (AICM) which is an extension of the existing ICM method to predict the future propagation pattern of multimedia (YouTube) content based on scraped social network (Facebook) user profiles in terms of their “talkativeness” and “influential power”. Simulation results suggest that the proposed AICM is reasonable and consistent.
A robust public watermark for halftone images

In many printing and publishing applications, it is desirable to embed data in halftone images for copyright control and authentication purposes. While intentional attacks on printed matter may not be likely, unintentional attacks such as cropping and distortion due to dirt or human writing/marking are likely. In this paper, we proposed a novel halftone image watermarking method called Watermarking Error Diffusion (WED) to embed a robust, invisible, public watermark in the parity domain of halftone images during halftoning while introducing minimal distortion. Since WED uses the local stochastic properties of the halftone image to embed the watermark throughout the whole image, WED is robust to cropping and distortion due to dirt or human writing/marking. Experimental results suggest that WED can give halftone images with good visual quality and the watermark is robust to crop and human marking.
Image Bit-Depth Enhancement via Maximum A Posteriori Estimation of AC Signal

When images at low bit-depth are rendered at high bit-depth displays, missing least significant bits needs to be estimated. We study the image bit-depth enhancement problem: estimating an original image from its quantized version from a minimum mean squared error (MMSE) perspective. We first argue that a graph-signal smoothness prior-one defined on a graph embedding the image structure-is an appropriate prior for the bit-depth enhancement problem. We next show that directly solving for the MMSE solution is, in general, too computationally expensive to be practical. We then propose an efficient approximation strategy. In particular, we first estimate the ac component of the desired signal in a maximum a posteriori formulation, efficiently computed via convex programming. We then compute the dc component with an MMSE criterion in a closed form given the computed ac component. Experiments show that our proposed two-step approach has improved performance over the conventional bit-depth enhancement schemes in both objective and subjective comparisons.
Color Video Denoising Based on Combined Interframe and Intercolor Prediction

An advanced color video denoising scheme which we call CIFIC based on combined interframe and intercolor prediction is proposed in this paper. CIFIC performs the denoising filtering in the RGB color space, and exploits both the interframe and intercolor correlation in color video signal directly by forming multiple predictors for each color component using all three color components in the current frame as well as the motion-compensated neighboring reference frames. The temporal correspondence is established through the joint-RGB motion estimation (ME) which acquires a single motion trajectory for the red, green, and blue components. Then the current noisy observation as well as the interframe and intercolor predictors are combined by a linear minimum mean squared error (LMMSE) filter to obtain the denoised estimate for every color component. The ill condition in the weight determination of the LMMSE filter is detected and remedied by gradually removing the “least contributing” predictor. Furthermore, our previous work on the LMMSE filter applied in the adaptive luminance-chrominance space (LAYUV for short) is revisited. By reformulating LAYUV and comparing it with CIFIC, we deduce that LAYUV is a restricted version of CIFIC, and thus CIFIC can theoretically achieve lower denoising error. Experimental results verify the improvement brought by the joint-RGB ME and the integration of the intercolor prediction, as well as the superiority of CIFIC over LAYUV. Meanwhile, when compared with other state-of-the-art algorithms, CIFIC provides competitive performance both in terms of the color peak signal-to-noise ratio and in perceptual quality.
Image bit-depth enhancement via maximum-a-posteriori estimation of graph AC component

While modern displays offer high dynamic range (HDR) with large bit-depth for each rendered pixel, the bulk of legacy image and video contents were captured using cameras with shallower bit-depth. In this paper, we study the bit-depth enhancement problem for images, so that a high bit-depth (HBD) image can be reconstructed from an input low bit-depth (LBD) image. The key idea is to apply appropriate smoothing given the constraints that reconstructed signal must lie within the per-pixel quantization bins. Specifically, we first define smoothness via a signal-dependent graph Laplacian, so that natural image gradients can nonetheless be interpreted as low frequencies. Given defined smoothness prior and observed LBD image, we then demonstrate that computing the most probable signal via maximum a posteriori (MAP) estimation can lead to large expected distortion. However, we argue that MAP can still be used to efficiently estimate the AC component of the desired HBD signal, which along with a distortion-minimizing DC component, can result in a good approximate solution that minimizes the expected distortion. Experimental results show that our proposed method outperforms existing bit-depth enhancement methods in terms of reconstruction error.
On the determination of capacity parameters in PEE-based reversible image watermarking

In the existing prediction-error expansion (PEE)-based reversible image watermarking schemes, the capacity parameters are determined in a recursive manner by gradually turning these parameters to fit the payload. This class of method needs multiple rounds of embedding iterations, and hence, it is computationally inefficient. In addition, when multiple capacity parameters need to be handled, the previous methods are generally not capacity-distortion optimized. In this work, we formulate the task of determining the capacity parameters as a capacity-distortion optimization problem, which can be shown to be convex. We also prove that under some conditions, even simple analytical solutions exist.
Fast mode decision and motion estimation for H.264 (FMDME)

The H.264 video coding standard achieves highest coding gain. In addition to common tools in previous standards such as H.263 and MPEG4, it supports multiple frames, multiple block sizes, and 1/4 pixel motion estimation, deblocking filter, intra-prediction, and so on. However, full search of for all block modes and reference frames requires heavy computational complexity. The algorithm predictive motion vector field adaptive search technique (PMVFAST) (Tourapis, 2000) was previously accepted into MPEG standard to achieve hundreds of time of speed up. FMBME (Chang, 2004), and some other algorithms (Yanfei Shen, 2004) have been developed to do fast multiple block size motion estimation. For multiple reference frame motion estimation, FMFME (Chang, 2003), and some other algorithms (Xiang Li, 2004) have also been developed. In this paper a new algorithm is presented named as fast mode decision and motion estimation (FMDME). This algorithm achieves high speed up factor by involving fast skip mode checking, fast multiple block size motion estimation, fast multiple reference frame selection, fast motion estimation, and fast intra-block skipping for P frame in H.264
Novel H.26X optimal rate control for low-delay communications

The existing rate control schemes in the literature calculates the quantization parameters of macro-blocks (MB) based on the quadratic/log rate models. Actually, this model may not be good because this model does not estimate well at some particular bit rates. This work investigates the relationships of bit rate and distortion with the MB quantization step size and standard deviation of MB prediction errors. We find that the linear rate and linear distortion models are established. Then we present the proposed rate control schemes based on these models. The proposed algorithm introduces a low quantization overhead, low computation complexity to calculate the optimal quantization step size, independence of the distortion factors and low memory usage compared with TMN8 rate control. The experimental results suggests that our scheme can achieve PSNR gain over TMN8.
An analytical framework for frame-level dependent bit allocation in hybrid video coding

In this paper, an analytical framework for frame-level dependent bit allocation (DBA) in hybrid video coding is proposed. First, the dependency of neighboring frames is quantitatively measured with the proposed inter-frame dependency model (IFDM). Based on the proposed IFDM, the problem of frame-level DBA among a number of frames of different frame types is studied, and the optimal solution is achieved through successive convex optimization. The prove the validity of the proposed framework, a case study of current state-of-the-art standard H.264/AVC is conducted. Experimental results show that significant gain of up to 0.9dB in PSNR can be obtained.
A Fast Converging Algorithm for Acoustic Echo Cancellation in Time-Varying Channels

In this paper, we propose an acoustic echo cancellation method called MPNLMS++ which can adapt to time varying channels with fast convergence. The MPNLMS++ can converge much faster than conventional algorithms when the channel changes from dispersive to sparse, and at least as fast as other fast algorithms in other situations. The effectiveness of MPNLMS++ is verified in the simulation.