Due to the increased popularity of augmented and virtual reality experiences, the interest in capturing the real world in multiple dimensions and in presenting it to users in an immersible fashion has never been higher. Distributing such representations enables users to freely navigate in multi-sensory 3D media experiences. Unfortunately, such representations require a large amount of data, not feasible for transmission on today’s networks. Efficient compression technologies well adopted in the content chain are in high demand and are key components to democratize augmented and virtual reality applications. Moving Picture Experts Group, as one of the main standardization groups dealing with multimedia, identified the trend and started recently the process of building an open standard for compactly representing 3D point clouds, which are the 3D equivalent of the very well-known 2D pixels. This paper introduces the main developments and technical aspects of this ongoing standardization effort.

/pdf/emerging-mpeg-standards-for-point-cloud-compression-3ik60bpn8o.pdf

Emerging MPEG Standards for Point Cloud Compression

Image demosaicing is a problem of interpolating full-resolution color images from so-called color-filter-array
(CFA) samples Among various CFA patterns, Bayer pattern has been the most popular choice and demosaicing
of Bayer pattern has attracted renewed interest in recent years partially due to the increased availability of source
codes/executables in response to the principle of "reproducible research" In this article, we provide a systematic
survey of over seventy published works in this field since 1999 (complementary to previous reviews22, 67)
Our review attempts to address important issues to demosaicing and identify fundamental differences among
competing approaches Our findings suggest most existing works belong to the class of sequential demosaicing
- ie, luminance channel is interpolated first and then chrominance channels are reconstructed based on recovered
luminance information We report our comparative study results with a collection of eleven competing
algorithms whose source codes or executables are provided by the authors Our comparison is performed on
two data sets: Kodak PhotoCD (popular choice) and IMAX high-quality images (more challenging) While
most existing demosaicing algorithms achieve good performance on the Kodak data set, their performance on
the IMAX one (images with varying-hue and high-saturation edges) degrades significantly Such observation
suggests the importance of properly addressing the issue of mismatch between assumed model and observation
data in demosaicing, which calls for further investigation on issues such as model validation, test data selection
and performance evaluation

http://www4.comp.polyu.edu.hk/~cslzhang/paper/conf/demosaicing_survey.pdf

Image demosaicing: a systematic survey

Mean opinion score (MOS) has become a very popular indicator of perceived media quality. While there is a clear benefit to such a "reference quality indicator" and its widespread acceptance, MOS is often applied without sufficient consideration of its scope or limitations. In this paper, we critically examine MOS and the various ways it is being used today. We highlight common issues with both subjective and objective MOS and discuss a variety of alternative approaches that have been proposed for media quality measurement.

Mean opinion score (MOS) revisited: methods and applications, limitations and alternatives

We present an encoding framework which exploits semantics for video content delivery. The video content is organized based on the idea of main content message. In the work reported in this paper, the main content message is extracted from the video data through semantic video analysis, an application-dependent process that separates relevant information from non relevant information. We use here semantic analysis and the corresponding content annotation under a new perspective: the results of the analysis are exploited for object-based encoders, such as MPEG-4, as well as for frame-based encoders, such as MPEG-1. Moreover, the use of MPEG-7 content descriptors in conjunction with the video is used for improving content visualization for narrow channels and devices with limited capabilities. Finally, we analyze and evaluate the impact of semantic video analysis in video encoding and show that the use of semantic video analysis prior to encoding sensibly reduces the bandwidth requirements compared to traditional encoders not only for an object-based encoder but also for a frame-based encoder.

http://www.eecs.qmul.ac.uk/~andrea/papers/cavallaro_CSVT_semantic_encoding.pdf

Semantic video analysis for adaptive content delivery and automatic description

Accurate measurement of the perceived quality of audio-visual services at the end-user is becoming a crucial issue in digital applications due to the growing demand for compression and transmission of audio-visual services over communication networks. Content providers strive to offer the best quality of experience for customers linked to their different quality of service (QoS) solutions. Therefore, developing accurate, perceptual-based quality metrics is a key requirement in multimedia services. In this paper, we survey state-of-the-art signal-driven perceptual audio and video quality assessment methods independently, and investigate relevant issues in developing joint audio-visual quality metrics. Experiments with respect to subjective quality results have been conducted for analyzing and comparing the performance of the quality metrics. We consider emerging trends in audio-visual quality assessment, and propose feasible solutions for future work in perceptual-based audio-visual quality metrics.

Perceptual-based quality assessment for audio-visual services: A survey

In this paper, we compared two subjective assessment methods DSCQS(Double Stimulus Continuous Quality Scale method) and ACR(Absolute Category Rating). These methods are widely used in order to evaluate video quality for multimedia application. We performed subjective quality tests using DSCQS and ACR methods. The subjective scores obtained by the DSCQS and ACR methods show that these methods are highly correlated in terms of MOS(Mean Opinion Score) and have slightly lower correlation in terms of DMOS(Difference Mean Opinion Score). The results indicate that ACR method is an effective subjective quality assessment method, which shows compatible performance with DSCQS method and can evaluate a larger number of video sequences.

/pdf/comparison-of-subjective-video-quality-assessment-methods-3nypt3psw3.pdf

Comparison of subjective video quality assessment methods for multimedia applications

We propose a new method for an objective measurement of video quality. By analyzing subjective scores of various video sequences, we find that the human visual system is particularly sensitive to degradation around edges. In other words, when edge areas of a video sequence are degraded, evaluators tend to give low quality scores to the video, even though the overall mean squared error is not large. Based on this observation, we propose an objective video quality measurement method based on degradation around edges. In the proposed method, we first apply an edge detection algorithm to videos and locate edge areas. Then, we measure degradation of those edge areas by computing mean squared errors and use it as a video quality metric after some postprocessing. Experiments show that the proposed method significantly outperforms the conventional peak signal-to-noise ratio (PSNR). This method was also independently evaluated by independent laboratory groups in the Video Quality Experts Group (VQEG) Phase 2 test. The method consistently provided good performances. As a result, the method was included in international recommendations for objective video quality measurement.

Objective video quality assessment

It has been shown that image compression based on principal component analysis (PCA) provides good compression efficiency for hyperspectral images. However, PCA might fail to capture all the discriminant information of hyperspectral images, since features that are important for classification tasks may not be high in signal energy. To deal with this problem, we propose a hybrid compression method for hyperspectral images with pre-encoding discriminant information. A feature extraction method is first applied to the original images, producing a set of feature vectors that are used to generate feature images and then residual images by subtracting the feature-reconstructed images from the original ones. Both feature images and residual images are compressed and transmitted. Experiments on data from the Airborne Visible/Infrared Imaging Spectrometer sensor indicate that the proposed method provides better compression efficiency with improved classification accuracy than conventional compression methods.

/pdf/hybrid-compression-of-hyperspectral-images-based-on-pca-with-34piqvb0p5.pdf

Hybrid Compression of Hyperspectral Images Based on PCA With Pre-Encoding Discriminant Information

We propose a new deinterlacing algorithm with selective motion compensation. It has been reported that deinterlacing methods using motion compensation produce significantly improved results, although they tend to yield undesired results in fast moving areas. This is due to weak correlations between the previous and current frames. The proposed algorithm solves this problem by selectively applying motion-compensated deinterlacing. We first apply intrafield interpolation in the spatial domain, and then selectively apply motion compensations according to the type of motion vectors. Experimental results show that the proposed method produces noticeably improved performance compared to existing motion-compensated deinterlacing methods.

Taeuk Jeong

Papers

Comparison of subjective video quality assessment methods for multimedia applications

Objective video quality assessment

Hybrid Compression of Hyperspectral Images Based on PCA With Pre-Encoding Discriminant Information

Deinterlacing with selective motion compensation

Deinterlacing with Selective Motion Compensation