nils-herrmann/clean_scirepeval huggingface dataset:
A symmetric key watermark for halftone images

In many printer and publishing applications, it is desirable to embed data in halftone images for copyright control and authentication purposes. While intentional attacks on printed matters 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 watermark in the parity domain of halftone images with symmetric key during halftoning while introducing minimal distortion.
Analytical study of RGB vertical stripe and RGBX square-shaped subpixel arrangements

The frequency characteristics of subpixel-based decimation with RGB vertical stripe and RGBX square-shaped subpixel arrangements are studied. To achieve higher apparent resolution than pixel-based decimation, the sampling locations are specially chosen for each of two subpixel arrangements, resulting in relatively small magnitudes of horizontal and vertical aliasing spectra in frequency domain. Thanks to 2-D RGBX square-shaped subpixel arrangement, all the horizontal, vertical, diagonal and anti-diagonal aliasing spectra merely contain low-frequency information, indicating that subpixel-based decimation with RGBX square-shaped panel is more effective in retaining original high frequency details than RGB vertical stripe subpixel arrangement.
PI-preserve data hiding for halftone image

In this paper, we propose a new data hiding algorithm for halftone images, namely pattern-and-intensity-preserve data hiding (Pi-preserve) which hides data without the help of original grayscale image. In this system, we introduce the pattern-preserve method to hide data and image dependent code error sensitive (IDC/sub ES/) to enhance the security and sensibility to error. It achieves a considerably high visual quality, and has a better performance in terms of modified peak-signal-to-noise ratio (MPSNR) when compared with data hiding self toggling (DHST) and data hiding smart pair toggling (DHSPT) [Ming Sun Fu, April 2002]. The complexity is relatively low as no connectivity measurement is needed in the embedding process. Pi-preserve is suitable for data authentication.
A fast intermode decision algorithm based on analysis of inter prediction residual

Rate-distortion-optimized (RDO) intermode decision is one of the most effective tools that greatly improves the coding performance of modern coding standards, for example, H.264/AVC and HEVC. However, RDO intermode decision also leads to extremely intense computation. To reduce the complexity, a fast intermode decision algorithm is presented in this paper. Mathematical analysis of inter prediction residual is performed which explicitly shows the impact of edge information and motion characteristics to the prediction accuracy. Moreover, It is shown that with fixed quantization step that minimizing of R-D costs over different partition types is equivalent to minimizing the variance of transformed residual which can be expressed by motion vector and edge gradient components. In consequence, the complex calculation of rate and distortion is replaced by simple pre-analysis of video content. The repetition of motion estimation (ME) and entropy coding process are avoided. Inspired by the theoretical analysis, a fast inter mode decision algorithm is proposed. Experimental results show that the fast method achieves considerable complexity reduction with negligible coding performance degradation.
A diamond search windowbased adaptive search range algorithm

In this paper, a novel diamond search window (SW) based full search algorithm is proposed. To dynamically adjust the size of the diamond search window, a frame level adaptive search range (SR) algorithm is presented. Laplace distribution is used to model the optimal motion vector difference (MVD) distribution within a frame and the model parameters are estimated by maximum likelihood estimation (MLE). The data used for MLE is also carefully studied. With the estimated distribution model, proper SR is obtained dynamically frame by frame. Experiment results show that a diamond SW outperforms the traditional squared SW. Also, the proposed adaptive search range algorithm properly adjusts the diamond SW size. The proposed diamond SW based adaptive search range (ASR+DSW-FS) algorithm obtains the same or even better performance compared with conventional full search algorithm, while significantly reduces the computational complexity.
Maximum a Posteriori Based (MAP-Based) Video Denoising VIA Rate Distortion Optimization

In this paper, a maximum a posteriori based (MAP-based) video denoising algorithm is proposed. According to the Bayes rule, the MAP estimate is determined by two terms: noise conditional density model and priori conditional density model. Based on the assumptions that the noise satisfies Gaussian distribution and the priori model is measured by the bit rate, the MAP estimate can be expressed as a rate distortion optimization problem. In order to find a suitable Lagrangian parameter, we re-write the problem as a constraint minimization problem by setting the rate as an objective function and the distortion as a constraint. In this way, we find that the Lagrangian parameter is determined by the distortion constraint. Fixing the distortion constraint, we can get the optimal Lagrangian parameter, which leads to the optimal denoising result. Some experiments are conducted to demonstrate the efficiency and effectiveness of the proposed method.
Predicting YouTube content popularity via Facebook data: A network spread model for optimizing multimedia delivery

The recent popularity of social networking websites have resulted in a greater usage of internet bandwidth for sharing multimedia content through websites such as Facebook and YouTube. Moving large volumes of multi-media data through limited network resources remains a technical challenge to this day. The current state-of-art solution in optimizing cache server utilization depends heavily on efficient caching policies to determine content priority. This paper proposes a Fast Threshold Spread Model (FTSM) to predict the future access pattern of multi-media content based on the social information of its past viewers. The prediction results are compared and evaluated against ground truth statistics of the respective YouTube video. A complexity analysis on the proposed algorithm for large datasets along with the correlation between Facebook social sharing and YouTube global hit count are explored.
Adaptive Block Coding Order for Intra Prediction in HEVC

In this paper, an adaptive block coding order for intra prediction is proposed. Modern video coding standards, including the most recent High Efficiency Video Coding (HEVC), utilize fixed scan orders in processing blocks during intra coding. However, the fixed scan orders typically result in residual blocks with noticeable edge patterns. That means the fixed scan orders cannot fully exploit the content-adaptive spatial correlations between adjacent blocks, thus the bitrate after compression tends to be large. To reduce the bitrate induced by inaccurate intra prediction, the proposed approach adaptively chooses both the block and subblock coding orders by minimizing the coding cost. Specifically, determining the block coding order is formulated as a traveling salesman problem that is solved using dynamic programming. Besides the block coding order, we also design the subblock coding order in each block with an adaptive manner. The experimental results demonstrate a Bjøntegaard-Delta-rate reduction of up to 4.4% compared with HEVC anchor.
Video denoising based on transform domain minimum mean square error

Denoising is one of the most common and important tasks in video processing systems and abundant efforts have been made on video denoising nowadays. In this paper, we propose a novel denoising scheme based on minimum mean square error (MMSE) filter in the 2D transform domain, which we call 2DTD-MMSE. The current input noisy frame is processed block-by-block, and for every block, the current noisy observation and multiple prediction blocks found by motion estimation (ME) in denoised previous frames as well as noisy future frames constitute a 2D observed representation array. Afterwards, 2D transform is applied to every block in the representation array, and every transform coefficient of current block is estimated by weighted average of the coefficients in the same frequency position of all the transformed blocks. The weighting coefficients are adaptively determined through MMSE for every block after the estimation of statistical parameters in the transform domain. Experimental results on commonly used test sequences demonstrate that the proposed 2DTD-MMSE achieves comparable or favorable performance when compared to several state-of-the-art algorithms.
Exploitation of inter-color correlation for color image demosaicking

Image demosaicking or color filter array interpolation is a process of interpolating missing color samples to reconstruct a full color image. In general, existing algorithms assume that the high frequency components such as edges, texture etc. of different color channels are similar and thus take an advantage of it to estimate the missing samples. In this paper, we efficiently analyze the relationships of intra and inter-color correlation among the channels and observe that such assumption fails in most cases. In view of this observation, we propose a scheme that exploits the correlation between different color channels much effectively than the existing algorithms. Experimental results demonstrate that the proposed algorithm outperforms the existing methods both in terms of Peak Signal to Noise Ratio (PSNR) and visual perception.
Adaptively Switching Between Directional Interpolation and Region Matching for Spatial Error Concealment Based on DCT Coefficients

In this paper, a novel spatial error concealment algorithm, which adaptively switches between directional interpolation and region matching, is proposed. Different from the previous spatial error concealment methods, which just utilize smooth property, the algorithm exploits both smooth property and texture information to recover the lost blocks. Based on the DCT coefficients in the available neighboring MBs, the algorithm automatically analyzes whether the MB is "smooth-like" or "texture-like" and adaptively select directional interpolation or region matching to recover the lost MB. The proposed algorithm has been evaluated on H.264 reference software JM 9.0. The experimental results demonstrate that the proposed method can achieve better PSNR performance and visual quality, compared with weighted pixel average (WPA) which is adopted in H.264, directional interpolation-only and region matching-only
Interpolation based symmetrical predictor structure for lossless image coding

Predictor based algorithms reported in literature uses only causal pixels and hence a non-symmetrical predictor structure for prediction. We observed that the performance of predictor is highly dependent on the predictor structure used. In view of this, we propose a novel interpolation based prediction scheme that enables us to use symmetrical predictor structure. In this sense, we have also used non causal pixels in our scheme. Also, from various interpolation algorithms available, we selected a simple one to ensure decoder simplicity, without any significant loss in performance. From performance evaluation, we found that our algorithm is significantly better in terms of compression performance as compared to some of the computationally complex methods.
Capacity for JPEG2000-to-JPEG2000 images watermarking

A data capacity estimation method is proposed for image watermarking. The data capacity is maximum number of bits that can be embedded in an image such that the image has no perceptual loss. It is assumed that the input is a JPEG2000 image file and after watermark embedding, the image is JPEG2000-compressed using the same quantization factors. This is called JPEG2000-to-JPEG2000 (J2K2J2K) watermarking. A human visual systems (HVS) model is used to estimate the just noticeable difference (JND) of each discrete wavelet transform (DWT) coefficients.
Backward error concealment of redundantly coded video

Error concealment at the video decoder is to recover erroneous picture region based on correctly decoded region in the same frame or the neighboring frames. However, error concealment cannot give satisfactory result in some cases, e.g. when a whole frame is lost. In this paper, we propose a novel backward error concealment method. While the existing temporal error concealment methods recover an erroneous frame by using its reference frame, the proposed method uses a refreshed future frame to recover the previous corrupted reference frame. This is based on the observation that a future frame can be recovered before its reference frame when some error resilience tools such as intra refresh or redundant picture are used. The advantage of the proposed method is that it can recover most pixels in the corrupted reference frame by inverse motion compensation without any error, since typically the refreshed future frame has both MVs and the residues. In the experiments, the proposed method achieves up to 1.0dB gain over the state-of-the-art temporal error concealment method.
Fast SOLA-based time scale modification using Modified Envelope Matching

Time scale modification (TSM) of speech and audio is useful in many applications. Synchronized Overlap-and-Add (SOLA) is a time-domain TSM algorithm known to achieve good speech and audio quality. One problem of SOLA is that it requires a large amount of computation. In this paper, we propose a technique called Modified Envelope-Matching TSM (MEM-TSM) to simplify the computation. The. MEM-TSM improves the previously proposed EM-TSM in quality and speed up factor. The proposed algorithm can reduce computation by 300 times with good perceptual quality of time-scaled speech and audio. Our experimental results show that the quality of MEM-TSM is almost the same as SOLA.
Highly efficient predictive zonal algorithms for fast block-matching motion estimation

Motion estimation (ME) is an important part of any video encoding system since it could significantly affect the output quality of an encoded sequence. Unfortunately, this feature requires a significant part of the encoding time especially when using the straightforward full search (FS) algorithm. We propose two techniques, the generalized motion vector (MV) predictor and the adaptive threshold calculation, that can be used to significantly improve the performance of many existing fast ME algorithms. In particular, we apply them to create two new algorithms, named advanced predictive diamond zonal search and predictive MV field adaptive search technique, respectively, which can considerably reduce, if not essentially remove, the computational cost of ME at the encoder, while at the same time give similar, and in many cases better, visual quality with the brute force full search algorithm. The proposed algorithms mainly rely upon very robust and reliable predictive techniques and early termination criteria with parameters adapted to the local characteristics combined with the zonal based patterns. Our experiments verify the considerable superiority of the proposed algorithms versus the performance of possibly all other known fast algorithms, and FS.
Palette-based compound image compression in HEVC by exploiting non-local spatial correlation

Non-camera captured images (also known as compound image) contain a mixture of camera-captured natural images and computer-generated graphics and texts. Nowadays, there are more and more applications calling for non-camera captured image/video compression scheme. However, current video coding standards, which are designed for natural video, treat non-camera captured video less carefully. For example, the state-of-the-art video coding standard High Efficiency Video Coding (HEVC) may blur or even remove edges in text/graphic region. A lot of schemes are proposed to preserve direction property of texts and graphics, such as palette-based intra coding. In this paper, a novel palette coding scheme is proposed for palette-based intra coding in HEVC. The palette in a block is predicted from an adaptive palette template, which records the statistical non-local spatial correlation of an image. Every block chooses its own palette using the palette template as the prediction in a rate-distortion optimized manner. Experimental results show that the proposed scheme can achieve up to 5.2% bit-rate saving compared to the state-of-the-art palette-based coding scheme in HEVC.
Combined Inter-frame and Inter-color Prediction for Color Video Denoising

An advanced color video denoising scheme which we call CIFIC based on combined inter-frame and inter-color prediction is presented in this paper. CIFIC performs the denoising filtering in the RGB color space, and exploits both the inter-frame and inter-color 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 noise-robust motion estimation (ME) which acquires a single motion trajectory for the RGB components. Then the current noisy observation as well as the inter-frame and inter-color predictors are combined by a linear minimum mean squared error (LMMSE) filter to obtain the denoised estimate for every color component. The experimental results verify that CIFIC provides competitive performance both in terms of the objective metric and in perceptual quality when compared with other state-of-the-art algorithms.
Modified distortion redistribution problem for High Efficiency Video Coding(HEVC)

Adaptive quantization matrix design for different block sizes is one of the possible methods to improve the RD performance in video coding and has recently attracted the focus of many researchers. In this paper, we first analyze the shortcomings of the evenly distributed distortion method which was proposed recently. In order to tackle these problems, we propose two modified methods, method I with relaxed distortion constraints and method II is iterative boundary distortion minimization problem considering variance adaptively. Both problems can be solved using convex optimization effectively and efficiently. Simulations have been conducted based on HM4.0, which is the reference software of the latest High Efficiency Video Coding (HEVC). Simulation results show the effect of our proposed methods. Both methods show their significance when evaluated by RD performance.
Temporal interpolation of video sequences using zonal based algorithms

Temporal interpolation has been proposed as a solution for increasing temporal resolution or even for predicting missing or corrupted frames within a video sequence. In this paper new techniques on temporal interpolation are presented, by mainly exploiting properties of the very popular and highly efficient zonal based motion estimation algorithms, and by introducing several other techniques such as multihypothesis motion compensation, motion classification and temporal/spatial filtering. In addition we further give an analysis on when temporal interpolation should be employed, thus possibly avoiding unwanted artifacts created from this process, while at the same time significantly improving the overall performance of the interpolation.
Cryptanalysis of chaotic convolutional coder

In this paper, we evaluate the security of a recently proposed joint error correction and encryption approach called chaotic convolutional coder, which integrates the chaotic encryption into the convolutional coding. We show that the probability of recovering the key vector controlling the chaotic switch is at least 0.289 under known-plaintext attack, if the number of available plaintext/ciphertext pairs p is equal to the constraint length k of the chaotic convolutional coder. In the case that p = k + e, where e > 0, we prove that the probability to recover the key vector is lower bounded by 1–2−e. We also consider the security of the chaotic con-volutional coder under chosen-plaintext attack. We propose two approaches to efficiently derive the key vector without leaving tractable pattern to the register. In particular, one of these two methods based on an efficient erasure code is capable of recovering the key vector with complexity of order O(k log k).
Low-band-shift (LBS) motion estimation with symmetric padding in wavelet domain

Low-band-shift (LBS) is a very efficient technique to compute and store the wavelet coefficients of all the shifted versions of an image. It makes it possible to perform motion estimation (called LBSME) directly in wavelet domain overcoming the shift variant property of discrete wavelet transform. However, when motion vectors of boundary wavelet blocks point outside the image boundaries, LBSME does not work well. In this paper, we proposed an algorithm called LBSME-SP to combine LBSME with symmetric padding to minimize the effects of boundary discontinuities. Consequently, the LBS structure is modified. Simulation results suggest that the proposed LBSME-SP can give considerable PSNR gain with only minor additional computation.
Robust speech recognition based on the second-order difference cochlear model

MFCC (Mel-Frequency Cepstral Coefficients) is a kind of traditional speech feature widely used in speech recognition. The error rate of the speech recognition algorithm using MFCC and CDHMM is known to be very low in a clean speech environment, but it increases greatly in a noisy environment, especially in the white noisy environment. We propose a new kind of speech feature called the auditory spectrum based feature (ASBF) that is based on the second-order difference cochlear model of the human auditory system. This new speech feature can track the speech formants and the selection scheme of this feature is based on both the second-order difference cochlear model and primary auditory nerve processing model of the human auditory system. In our experiment, the performance of MFCC and ASBF are compared in both clean and noisy environments when left-to-right CDHMM with 6 states and 5 Gaussian mixtures is used. The experimental result shows that the ASBF is much more robust to noise than MFCC. When only 5 frequency components are used in ASBF, the error rate is approximately 38% lower than the traditional MFCC with 39 parameters in the condition of S/N=10 dB with white noise.
Fast global motion estimation based on local motion segmentation

In MPEG-4, global motion estimation (GME) and global motion compensation can improve the visual quality of local motion estimation/compensation. However, the computational complexity of GME is very high. Even the existing fast algorithm, FFRGMET, in the MPEG-4 OM3 software is not fast enough. In this paper, we propose a fast GME algorithm called APSGME. It uses motion vectors from the PMVFAST local motion estimation to perform early termination, foreground/background block-based segmentation, feature point selection. Experimental results shown that APSGME can achieve considerable speed-up over FFRGMET while improving the visual quality simultaneously.
Motion compensated temporal interpolation with overlapping

Common techniques such as frame repetition or linear interpolation for reconstructing skipped frames in temporally subsampled video sequence tend to introduce undesirable artifacts. A previously proposed technique, motion compensated temporal interpolation (MCTI), can interpolate video frames in time domain with good interpolated image quality. However, the reconstructed frames tend to be blocky. In this paper, we proposed to incorporate an overlapping technique to solve the problem. The resulting technique, overlapped motion compensated temporal interpolation (OMCTI), was found in simulation to give significantly reduced blocking artifacts.