nils-herrmann/clean_scirepeval huggingface dataset:
Video quality monitoring of streamed videos

This paper describes a video quality analysis system for inservice monitoring of streamed videos, particularly over mobile/wireless networks. The algorithm adopts the no-reference method, and enables real-time measurement of video quality at any point in the content production and delivery chain using any given video. The technologies developed include no-reference methods for measuring picture freeze, picture loss, and blockiness. The developed system (where the software has not been optimized for speed) is able to process video of CIF size (352×288 pixels) at more than 30 fps on a Pentium-IV 3GHz computer. The experimental results show that the proposed video quality analysis system gives good accuracy for picture freeze, picture loss, and blocking detections.
Comparison of Video Quality Metrics on Multimedia Videos

The state-of-the-art objective video quality metrics reported in the literature have so far been focused on TV signals with large frame sizes, full TV frame rates, and high compressed bit rates. The aim of this paper is to present the performance of three widely-known objective video quality metrics but tested on multimedia videos with small frame sizes, various frame rates, and low bit rates. The video quality metrics used were the NTIA video quality metrics (the "general" and the "videoconferencing" models), a modified Watson's DVQ metric, and the VSSIM metric. The test videos consist of both H.264 and MPEG-4 compressed videos with GIF and QCIF frame sizes, at various bit rates (24 kbps-384 kbps) and frame rates (7.5 fps-30 fps). Here, results and conclusions derived from the comparison of the three metrics will be provided.
3D shape modeling by color phase stepping light projection

Color encoded phase-stepping light projection method is a new and promising technique for 3D shape modeling However, the 3D model acquired is often smeared by large error. The main cause of the error is color coupling amongst the three primary colors RGB. In this paper, we first analyzed the color-coupling problem. It is found that there is a strong coupling between G and R element. The coupling between R and G are proportional to the phase interval between them and the overall intensity of image. Second, we proposed an adaptive phase stepping method to alleviate the color coupling errors efficiently and improve accuracy effectively. An algorithm corresponding to a specific paradigm with R-G-B phase step set to 0-45-180 is given and is applied to measure different objects. Experimental results demonstrate the effectiveness of the method.
IR face synthesis using motion vector field

Infrared (IR) imaging device provides natural motivation for illumination-free face recognition. In this study, a method that can create a new IR face view between two given IR face images taken at different view points is presented, using motion vectors. Unlike existing prior arts which utilize optical flow, the proposed method utilizes the block based matching method to obtain correspondence between the two given IR face images. In addition, interpolation algorithm is employed to make the sparse motion vector "dense". An iterative error correction method is developed to reduce the errors of motion vectors. There is no facial features detection involved in our system so that it is suitable for IR images in which facial features like eyes, nose are blurred. The proposed method can be used for IR face recognition, animation, etc.
Low bit rate quality assessment based on perceptual characteristics

Peak signal-to-noise ratio (PSNR) is not a good measure of perceived picture quality, especially at low bit rates of coding. This paper proposes a new approach for computing perceptual distortion for visual signal in order to provide an objective measure for perceptual quality at low bit rate coding in typically mobile communications. The regions with three major perceptually disturbing artifacts, namely, damaged edge, blockiness and ringing, are detected as the basis of assessment. The correlation of the metric with human perception has been demonstrated with low bit rate CIF test data.
Quality evaluation of MPEG-4 and H.26L coded video for mobile multimedia communications

This paper proposes a new approach for computing perceptual distortion for visual signal in order to provide an objective measure for perceptual quality at low bit rate MPEG-4 and H.26L coding in typically mobile multimedia communications. The regions with three major perceptually disturbing artefacts, namely, damaged edge, blockiness and ringing, are detected as the basis of assessment. The correlation of the metric with human perception has been demonstrated with low bit rate (24/spl sim/384 Kbps) CIF and QCIF test data.
Blind Image Blur Identification in Cepstrum Domain

The type and extent of blur affect image quality and therefore its evaluation. This paper presents an accurate method for blur identification and parameter estimation from one image without a priori knowledge. The key idea of the proposed method is to perform Fourier transform of logarithm spectrum to detect the periodic blur pattern in cepstrum domain instead of spectral nulls. Accordingly, the estimation of blur parameters is more accurate and robust to noise. The experimental results validate the accuracy of the proposed method.
Video quality metric for low bitrate compressed videos

Traditionally, peak signal-to-noise ratio (PSNR) has been used to represent the quality of a compressed video sequence. However, PSNR has been found to correlate poorly with subjective quality ratings, particularly at much lower bit rates and frame rates. This paper proposes an objective video quality metric to automatically measure the perceived quality of a stream of video images based on a combined measure of distortion-invisibility, block-fidelity, and content richness fidelity. The proposed method has been tested on CIF and QCIF video sequences compressed at low bit rates and frame rates and it is shown to give significantly better correlations to human perception than peak signal-to-noise ratio (PSNR).
Biologically inspired algorithm for enhancement of speech intelligibility over telephone channel

This paper describes a method to increase speech intelligibility when the speech signal is being transmitted over telephone lines. In order to detect all factors which affect speech intelligibility, we use telephone simulation tool in ITUT Software Tools Library release 2005 (STL2005) to identify the most problematic telephone-channel deteriorations. Of the various effects considered, additive noise and bandwidth of telephone channel seem to have the greatest influence on human's recognition accuracy. To reduce this degradation, a Lombard production and perception effect model, which represents the spectral changes of speech signal uttered and perceived in noisy environment, is proposed. This model is realized by a threestage modification procedure involving time-scale, pitch-scale, the formants and the consonant-vowel energy ratio modifications of the normal speech signals. From listening test conducted, it is shown that the proposed compensation algorithm increases the intelligibility of speech in telephone channel environments at 0 dB Signal-to-Noise ratio (SNR) and −10 dB SNR by nearly 5.5% and 13% over the unprocessed signals respectively.
Low-complexity global motion estimation based on content analysis

In this paper, we present a new approach for global motion estimation based on pre-analysis of the video content that works with compressed video data (e.g. MPEG-2). The novel idea is to perform pre-analysis of the scene content based on DCT coefficients without explicit MC-image reconstruction. Here, with the use of affine model and the combination of the spatial and temporal continuities of global motion parameters, accurate and robust dominant motion can be estimated and the outliers can be removed. Moreover, the problem of inaccurate initial descending direction estimation associated with the classical global motion estimation methods has been overcome. A global motion model, providing real-time performance, is achieved from decoded P-frame motion vector fields.
No-reference JPEG-2000 image quality metric

In this paper, a method for measuring the perceptual image quality of JPEG-2000 coded images has been proposed. The image quality is characterized by the average edge-spread in the image, or more specifically the average extent of the slope's spread of an edge in the opposing gradients' directions. The proposed method is, in effect, a way of measuring the amount of blurring in the image. The effectiveness of such method is validated using subjective tests and the experimental results show that the proposed method can provide results that correlate relatively well with human subjective ratings.
Just-noticeable-distortion profile with nonlinear additivity model for perceptual masking in color images

We propose a new spatial just noticeable distortion (JND) profile for color image processing. The JND threshold depends on various masking effects underlying existing in the human vision system (HVS). How to efficiently integrate different masking effects together is the key issue of modelling the JND profile. Based on recent vision research results, we model the masking effects in different stimulus dimensions as a nonlinear additivity model for masking (NAMM). It applies to all color components and accounts for the compound impact of luminance masking and texture masking to estimate the JND threshold in images. In our PSNR and subjective comparison to the related work, the proposed NAMM scheme provides a more accurate JND profile towards the actual JND bound in the HVS.
Blind Blur Assessment for Vision-Based Applications

This paper proposes a method for assessing blur caused by defocus from one image. The essential idea is to estimate the point spread function (PSF) from the line spread function (LSF), whereas the LSF is constructed from edge information. The procedure includes edge detection and localization, pixel interpolation, LSF determination and PSF extraction. This approach is independent of image contents, and the algorithm has fast speed as it works in spatial domain without complex Fourier transform or iterative computation. The experimental results validate the proposed method. It can be used for blind image quality evaluation in vision-based applications.
Adaptive nonlinear diffusion processes for ringing artifacts removal on JPEG 2000 images

JPEG 2000 image coding standard aims to achieve high compression performance. As the bit rate decreases, visual degradation caused by information loss on an image becomes more and more visible. We propose an adaptive nonlinear diffusion method to reduce ringing artifacts while preserving and enhancing image edges. The diffusion coefficient is the linear combination of three membership functions that correspond to the different gradient scales. The parameters are tuned using a stochastic optimization technique so that the diffusion coefficient can adapt to the given image data to achieve optimal restoration performance. Experimental results on JPEG 2000 compressed images have shown the effectiveness of the proposed nonlinear diffusion processes for ringing artifacts removal.
Contrast signal-to-noise ratio for image quality assessment

Peak signal-to-noise ratio (PSNR) is commonly used as an objective quality metric in signal processing. However, PSNR correlates poorly with the subjective quality rating. In this paper, we propose a new metric using contrast signal-to-noise ratio (CSNR), which measures the ratio of the contrast information level of distorted signal to the contrast level of the error signal. The performance of the proposed method has been verified using a database of images compressed with JPEG and JPEG 2000. The results show that it can achieve very good correlation with the subjective mean opinion scores in terms of prediction accuracy, monotonicity and consistency.
Visual distortion assessment with emphasis on spatially transitional regions

It is known that the human visual system (HVS) does not pay equal attention to each error and even region in judging picture quality. In this paper, we combine a perceptual model with an integrated detection of the spatially transitional regions in visual distortion evaluation to better match the HVS perception to visual quality. For decompressed images or video, the spatially transitional regions are the regions where major perceptually disturbing artefacts caused by edge impairments (mainly due to blurring and locations where the edge information is not adequately represented) and the presence of false edges (mainly due to blockiness and the presence of strong rippling effects of ringing) usually occur. Such regions are efficiently detected based on a single two-dimensional spatial high-pass filter in our work. Good correlation between the proposed method and the human perception has been demonstrated with the full set of 50-Hz video quality expert group test data.
Measuring blocking artifacts using edge direction information [image and video coding]

Block-based transform coding is the most popular approach for image and video compression. The objective measurement of blocking artifacts plays an important role in the design, optimization. and assessment of image and video coding systems. This paper presents a new algorithm for measuring blocking artifacts in images and videos. Instead of using the traditional pixel discontinuity along the block boundary, we use the edge directional information of the images. The new algorithm does not need the exact location of the block boundary thus is invariant to the displacement, rotation and scaling of the images. Experiments on various still images and videos show that the new blockiness measure is very efficient in terms of computational complexity and memory usage, and can produce blocking artifact measurement consistent with subjective rating
Recovery of compressed videos using forward and backward anisotropic diffusion

Many post-processing algorithms can efficiently reduce blocking artifacts but pay less attention to the sharpness of the image edges. In this paper, we propose a new post-processing method based on forward and backward anisotropic diffusion for reducing blocking, ringing effects and sharpening the edges. The proposed algorithm has been applied to the compressed video sequences for picture quality enhancement. Experimental results show that the proposed algorithm can efficiently improve the objective and subjective quality for different bit rate case
A no-reference quality metric for measuring image blur

In this paper, a method for measuring the perceptual quality of blurred images has been proposed. Here, the amount of image blur is characterized by the average extent of edges in the image, or more specifically the average extent of the slope's spread of an edge in the opposing gradients' directions. The effectiveness of such method is validated using subjective tests on blurred images, including JPEG-2000 coded images, and the experimental results show that the proposed method can provide results that correlate relatively well with human subjective ratings.
Perceptual Quality Evaluation on Periodic Frame-Dropping Video

In general, low and very-low bitrate video communication systems cannot achieve the full frame rate (25 Hz for PAL or 30 Hz for NSTC), which brings temporal distortion. The influence of reduced frame rate on subjective quality evaluation is a very important topic for both perceptual quality metrics and communication system optimization. In this paper, we present our work on the numerical modeling of the influence. The work includes two parts: first we measured the detectability and annoyance of periodic frame dropping's effect on perceptual visual quality evaluation under different content and frame size conditions. Then, a simple and effective feature is proposed to represent the content of video in temporal quality evaluation. The high Pearson and Spearman correlation results between the MOS and proposed model, as well as the results of other two error metrics, confirm the success of the selected temporal content-quality feature.
Integrated Evaluation of Temporal and Spatial Distortions for Low Bit-rate Videos

Most distortion/artifacts in low bit-rate compressed videos are strong and obvious to human eyes, and may even change the spatio-temporal structure of visual objects. Therefore it is important to evaluate the compound perceptual impact of spatial and temporal changes. Recent neurophysiological researches have found that the high-level spatial information (shape and depth, etc.) and temporal information (motion, etc.) are processed separately in two visual pathways in human brains. In this paper, spatial and temporal distortions are evaluated separately in two modules, and are then combined in an integration module. Two subjective viewing experiments are performed. One experiment is to evaluate the subjective quality on temporal distortion only, and second experiment is to evaluate the low bit-rate videos with both spatial and temporal distortions. Experimental results and the associated analysis show that the proposed visual quality metric is in good alignment with human perception
Local visual perceptual clues and its use in videophone rate control

We present a method for extracting local visual perceptual clues and its application for rate control of videophone, in order to ensure the scarce bits to be assigned for maximum perceptual coding quality. The optimum quantization step is determined with the rate-distortion model considering the local perceptual clues in the visual signal. For extraction of the perceptual clues, luminance adaptation and texture masking are used as the stimulus-driven factors, while skin color serves as the cognition-driven factor in current implementation. Both objective and subjective quality evaluations are given by evaluating the proposed perceptual rate control (PRC) scheme in the H.263 platform, and the evaluations show that the proposed PRC scheme achieves significant quality improvement in the block-based coding for bandwidth-hungry applications.
Perceptual-quality significance map (PQSM) and its application on video quality distortion metrics

The paper presents a new and general concept, PQSM (perceptual quality significance map), to be used in measuring visual distortion. It makes use of the mechanism that the HVS (human visual system) pays more attention to certain areas of visual signals due to one or more of the following factors: salient features in image/video; cues from domain knowledge; association of other media (e.g., speech or audio). PQSM is a 3D/4D array whose elements represent the relative perceptual-quality significance levels for the corresponding pixels/regions for images or video. Due to its generality, PQSM can be incorporated into any visual distortion metrics; it can improve effectiveness or/and efficiency of perceptual metrics or even enhance a PSNR-based metric. A three-stage PQSM generation method is also proposed, with an implementation of motion, luminance, skin-color and face mapping. Experimental results show that the scheme can significantly improve the performance of current image/video distortion metrics.
Image Quality Measure using Curvature Similarity

This paper proposes a new full-reference objective metric for image quality assessment. The reference and distorted images are decomposed into a number of wavelet subbands, in which mean curvatures and perceived error of the wavelet coefficients of two images are computed and integrated to give overall quality index. Taking structural similarity and error visibility into account, the new method can achieve high consistency with subjective evaluation compared with other metrics. Experimental results have shown the effectiveness of the proposed metric.
Perceptual quality metric for compressed videos

The paper proposes an objective perceptual video quality metric to assess the perceived quality of digital videos automatically. Traditionally, peak signal-to-noise ratio (PSNR) has been used to represent the quality of a compressed video sequence. However, PSNR has been found to correlate poorly with subjective quality ratings, particularly at much lower bit rates and frame rates. Computational models are applied to emulate human visual perception based on block-fidelity, content richness fidelity, spatial-textural, colour, and temporal maskings. The proposed video quality metric has been tested on CIF and QCIF video sequences compressed at various bit rates and frame rates. It has been shown to give significantly better correlation to human perception than PSNR.
Modelling visual attention and motion effect for visual quality evaluation

The perceptual visual quality evaluation of human visual system (HVS) is very complex. It concerns almost all aspects of visual processing in the vision path, from low-level neuron activities to high-level visual perception. Existing perceptual visual quality metrics (VQMs) only considered several of the mechanisms of HVS, and many others are ignored. In this paper, two global modulatory factors, visual attention and motion suppression, are modelled and combined to form a mathematic expression - perceptual quality significant level (PQSL). To a certain extent, it is believed that PQSL values reflect the processing ability of the human brain on local visual content. To evaluate their effects on visual quality evaluation, two VQMs are proposed. One is a MSE-like VQM based in a PQSL-modulated JND profile, which was proposed in (Z. K. Lu et al, Proc. ICASSP'2004, v.3, p.705-708, 2004); the other VQM is based on Wang's visual quality assessment (Sig. Proc.:Image Comm., v.19, n.2, p.121-132, 2004), PQSL values are used to adjust the weights of his structural similarity index. Experimental results show that introduction of the global modulatory factors can improve the performance of current visual quality metrics.
A locally-adaptive algorithm for measuring blocking artifacts in images and videos

Block transform coding is the most popular approach for image and video compression. The objective measurement of blocking artifacts plays an important role in the design, optimization, and assessment of image and video coding systems. This paper presents a new algorithm for measuring blocking artifacts in images and videos. It exhibits unique and useful features: 1) it examines the blocks individually so that it can measure the severity of blocking artifacts locally; 2) it is a one-pass algorithm in the sense that the image needs to be accessed only once; 3) it takes into account the blocking artifacts for high bit rate images and the flatness for the very low bit rate images; 4) the blocking artifacts measure is well-defined in the range of 0-10. Experiments on various still images and videos show that this blockiness measure is very efficient in terms of computational complexity and memory usage, and can produce consistent blocking artifacts measurement.