The measurement of meaning

Changing network conditions pose severe problems to video streaming in the Internet. HTTP adaptive streaming (HAS) is a technology employed by numerous video services that relieves these issues by adapting the video to the current network conditions. It enables service providers to improve resource utilization and Quality of Experience (QoE) by incorporating information from different layers in order to deliver and adapt a video in its best possible quality. Thereby, it allows taking into account end user device capabilities, available video quality levels, current network conditions, and current server load. For end users, the major benefits of HAS compared to classical HTTP video streaming are reduced interruptions of the video playback and higher bandwidth utilization, which both generally result in a higher QoE. Adaptation is possible by changing the frame rate, resolution, or quantization of the video, which can be done with various adaptation strategies and related client- and server-side actions. The technical development of HAS, existing open standardized solutions, but also proprietary solutions are reviewed in this paper as fundamental to derive the QoE influence factors that emerge as a result of adaptation. The main contribution is a comprehensive survey of QoE related works from human computer interaction and networking domains, which are structured according to the QoE impact of video adaptation. To be more precise, subjective studies that cover QoE aspects of adaptation dimensions and strategies are revisited. As a result, QoE influence factors of HAS and corresponding QoE models are identified, but also open issues and conflicting results are discussed. Furthermore, technical influence factors, which are often ignored in the context of HAS, affect perceptual QoE influence factors and are consequently analyzed. This survey gives the reader an overview of the current state of the art and recent developments. At the same time, it targets networking researchers who develop new solutions for HTTP video streaming or assess video streaming from a user centric point of view. Therefore, this paper is a major step toward truly improving HAS.

A Survey on Quality of Experience of HTTP Adaptive Streaming

Quality evaluation of underwater images is a key goal of underwater video image retrieval and intelligent processing. To date, no metric has been proposed for underwater color image quality evaluation (UCIQE). The special absorption and scattering characteristics of the water medium do not allow direct application of natural color image quality metrics especially to different underwater environments. In this paper, subjective testing for underwater image quality has been organized. The statistical distribution of the underwater image pixels in the CIELab color space related to subjective evaluation indicates the sharpness and colorful factors correlate well with subjective image quality perception. Based on these, a new UCIQE metric, which is a linear combination of chroma, saturation, and contrast, is proposed to quantify the non-uniform color cast, blurring, and low-contrast that characterize underwater engineering and monitoring images. Experiments are conducted to illustrate the performance of the proposed UCIQE metric and its capability to measure the underwater image enhancement results. They show that the proposed metric has comparable performance to the leading natural color image quality metrics and the underwater grayscale image quality metrics available in the literature, and can predict with higher accuracy the relative amount of degradation with similar image content in underwater environments. Importantly, UCIQE is a simple and fast solution for real-time underwater video processing. The effectiveness of the presented measure is also demonstrated by subjective evaluation. The results show better correlation between the UCIQE and the subjective mean opinion score.

An Underwater Color Image Quality Evaluation Metric

This paper offers a review of present achievements in the field of processing of ceramic-based materials with complex geometry using the main additive manufacturing (AM) technologies In AM, the geometrical design of a desired ceramic-based component is combined with the materials design In this way, the fabrication times and the product costs of ceramic-based parts with required properties can be substantially reduced However, dimensional accuracy and surface finish still remain crucial features in today's AM due to the layer-by-layer formation of the parts In spite of the fact that significant progress has been made in the development of feedstock materials, the most difficult limitations for AM technologies are the restrictions set by material selection for each AM method and aspects considering the inner architectural design of the manufactured parts Hence, any future progress in the field of AM should be based on the improvement of the existing technologies or, alternatively, the development of new approaches with an emphasis on parts allowing the near-net formation of ceramic structures, while optimizing the design of new materials and of the part architecture

Additive Manufacturing of Ceramic‐Based Materials

Quality is a very important parameter for all objects and their functionalities. In image-based object recognition, image quality is a prime criterion. For authentic image quality evaluation, ground truth is required. But in practice, it is very difficult to find the ground truth. Usually, image quality is being assessed by full reference metrics, like MSE (Mean Square Error) and PSNR (Peak Signal to Noise Ratio). In contrast to MSE and PSNR, recently, two more full reference metrics SSIM (Structured Similarity Indexing Method) and FSIM (Feature Similarity Indexing Method) are developed with a view to compare the structural and feature similarity measures between restored and original objects on the basis of perception. This paper is mainly stressed on comparing different image quality metrics to give a comprehensive view. Experimentation with these metrics using benchmark images is performed through denoising for different noise concentrations. All metrics have given consistent results. However, from representation perspective, SSIM and FSIM are normalized, but MSE and PSNR are not; and from semantic perspective, MSE and PSNR are giving only absolute error; on the other hand, SSIM and PSNR are giving perception and saliency-based error. So, SSIM and FSIM can be treated more understandable than the MSE and PSNR.

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Image Quality Assessment through FSIM, SSIM, MSE and PSNR—A Comparative Study

Quality assessment is a very challenging problem and will still as is since it is difficult to define universal tools. So, subjective assessment is one adapted way but it is tedious, time consuming and needs normalized room. Objective metrics can be with reference, with reduced reference and with no-reference. This paper presents a study carried out for the development of a no-reference objective metric dedicated to the quality evaluation of display devices. Initially, a
subjective study has been devoted to this problem by asking a representative panel (15 male and 15 female; 10 young
adults, 10 adults and 10 seniors) to answer questions regarding their perception of several criteria for quality assessment.
These quality factors were hue, saturation, contrast and texture. This aims to define the importance of perceptual criteria
in the human judgment of quality. Following the study, the factors that impact the quality evaluation of display devices have been proposed. The development of a no-reference objective metric has been performed by using statistical tools allowing to separate the important axes. This no-reference metric based on perceptual criteria by integrating some specificities of the human visual system (HVS) has a high correlation with the subjective data.

Toward an efficient objective metric based on perceptual criteria

Nowadays, the visual information is widely used for several applications such as medical diagnosis, video-surveillance...
This information needs to be displayed in order to exploit the contained data. So, the display devices market is growing very
quickly and the used technologies are different from a manufacturer to another. This leads to a need of a comparison between displays of different technologies but also ones from the same technology. In this paper, we describe two methodologies that we have used, for a subjective cross-media evaluation and a single media evaluation, in the context of image quality for display reproduction. We compare the results obtained by the two methodologies in order to determine if it is possible to replace a cross-media evaluation by a single media evaluation. We describe how we have used, the characterization of a display in order to simulate a display color reproduction on another one. We explain the different statistical non-parametric tests that we have used, to analyze the results. And we discuss about the results obtained for the two cases, and the possibility to replace a cross-media evaluation by a single-media evaluation.

Quality assessment of color reproduction devices: cross-media vs. single media

A New Quantification Method under Colorimetric Constraints.

In this work, a new stereo image coding technique is proposed. The new approach integrates the coding of the
residual image with the disparity map. The latter computed in the wavelet transform domain. The motivation
behind using this transform is that it imitates some properties of the human visual system (HVS), particularly,
the decomposition in the perspective canals. Therefore, using the wavelet transform allows for better perceptual
image quality preservation. In order to estimate the disparity map, we used a quadtree segmentation in each
wavelet frequency band. This segmentation has the advantage of minimizing the entropy. Dyadic squares in the
subbands of target image that they are not matched with other in the reference image constitutes the residuals
are coded by using an arithmetic codec. The obtained results are evaluated by using the SSIM and PSNR
criteria.

A wavelet-based quadtree driven stereo image coding

Quality assessment is becoming an important issue in the framework of image processing. This need is expressed
by the fact that the quality threshold of end-users has been shifted up because of the large availability of high
fidelity sensors at very affordable price. This observation has been made for different application domains such as
printing, compression, transmission, and so on. Starting from this, it becomes very important to manufacturers
and producers to provide products of high quality to attract the consumer. This high interest on quality means
that tools to measure it have to be available. This work is dedicated to the comparison of subjective methodologies
in the digital cinema framework. The main goal is to determine with a group of observers, which methodology is
better for assessing digital cinema content and what is the annoyance level associated to each of them. Several
configurations are tested side by side, Butterfly, one by one, Horizontal scroll, vertical scroll, Horizontal and
vertical scroll.

Mohamed-Chaker Larabi

Papers

Toward an efficient objective metric based on perceptual criteria

Quality assessment of color reproduction devices: cross-media vs. single media

A New Quantification Method under Colorimetric Constraints.

A wavelet-based quadtree driven stereo image coding

Comparison of subjective assessment protocols for digital cinema applications