Stereoscopic Video Quality Assessment Using Oriented Local Gravitational Force Statistics

This paper describes a Qt-based C++ application for full-reference stereoscopic video quality assessment. The application is platform independent and provides a friendly Graphical User Interface (GUI). The stereoscopic video signals used in the application are based in two-view model, such as the H.264/AVC standard with Multiview Video Coding (MVC), and several spatial resolutions are available. The application provides objective video quality algorithms, such as PSNR, SSIM and PW-SSIM and incorporates a recently published technique for stereoscopic video quality assessment, called disparity weighting (DW), DPSNR, DSSIM and DPW-SSIM. Numerical results corresponding to the performance of the objective measurements acquired using the proposed application are presented. The ultimate goal is that the application will contribute, as an open-source tool to be used by academia and industry, for standardization and development of objective algorithms and evaluation of impairments in stereoscopic video signals caused by some processing techniques.

With the consideration that incorporating visual saliency information appropriately can benefit image quality assessment metrics, this paper proposes an objective stereoscopic video quality assessment (SVQA) metric by incorporating stereoscopic visual attention (SVA) to SVQA metric. Specifically, based upon the multiple visual masking characteristics of HVS, a stereoscopic just-noticeable difference model is proposed to compute the perceptual visibility for stereoscopic video. Next, a novel SVA model is proposed to extract stereoscopic visual saliency information. Then, the quality maps are calculated by the similarity of the original and distorted stereoscopic videos’ perceptual visibility. Finally, the quality score is obtained by incorporating visual saliency information to the pooling of quality maps. To evaluate the proposed SVQA metric, a subjective experiment is conducted. The experimental result shows that the proposed SVQA metric achieves better performance in comparison with the existing SVQA metrics.

An experimental service of 3DTV cable broadcasting was made by delivering stereoscopic 3D video to the users in dual HD stream format. Also, an experimental attempt was made to provide backward compatibility for conventional 2D Set-top Boxes (STB) receiving and displaying only one stream of stereoscopic 3D video signal called reference video. For the experimental service, stereoscopic 3D video signals are encoded with 35 Mbps and transmitted over single broadcasting channel by using the existing cable headend and transmission systems. Prototypes of the software-based 3D encoder and 3D STB were also used for the experimental service. Through the experimental broadcasting service, it was possible to provide HD 3DTV broadcasting service under legacy cable environment and to support backward compatibility for the conventional 2D STBs to receive HD broadcasting by using the reference video. A survey revealed that about 60% of the viewers answered the image quality of stereoscopic 3D video in dual HD stream format was better than that in single HD stream format.

In this work, we propose a stereoscopic video streaming system that uses rateless codes (Raptor codes) as the error protection scheme. Initially, we model the rate-distortion (RD) curve of video encoder and performance of channel codec. Then, we estimated the distortion on the stereoscopic video quality caused by packet losses. Finally, analytical models and estimated single packet loss distortions are used to minimize the end-to-end distortion and obtain optimal encoder bit rates and unequal error protection (UEP) rates. The simulation results clearly demonstrates the significant quality gain against the non-optimized schemes.

Quality assessment of stereoscopic video in free viewpoint video system

The article proposes a universal approach to detect the presence of additional information attachments in the spatial domain of digital images. The approach is based on the use of the steganalytic method developed by the author earlier and based on the analysis of sequential triads of triplets in the matrix of unique colors of image. The steganoanalytic method Color Triads allows to detect with high accuracy the additional information attachments embedded by various steganographic methods into the spatial domain of images. The perturbations in the matrix of unique colors of images as a result of steganographic transformation are illustrated which concludes about the sensitivity of the blue color component even to small modifications of the brightness values of this matrix. The efficiency of detecting stegoes formed at small values of payload (0.4 bpp and less) based on LSB, S-UNIWARD, MiPOD and WOW steganographic methods is shown. The obtained results of computational experiments allow detect the filled color components of digital images with high accuracy even at payload of 0.1 and 0.05 bpp that is much higher than the results of modern analogues. The steganalytic method analyzes the spatial domain of images, which avoids the accumulation of computational errors that affect the detection result.

Currently, three-dimensional (3D) video is gaining increasing popularity by providing immersive user experience. Compared against conventional 2D video, 3D video excels at bringing a “live” scene closer to the users, and/or trying to place the users in the environment of the displayed content. However, streaming 3D video sequences over the IP networks is challenging due to the impact of dynamic network conditions on user quality. Accurate objective 3D video quality assessment is critical for advanced real-time video streaming adaptation solutions. Most state-of-the-art objective 3D video quality metrics are reference-based and require access to the original 3D video sequences, which is not possible for the real-time applications. This paper proposes the extended No-reference objective 3D Video Quality Metric (eNVQM) for real time 3D video quality assessment. eNVQM establishes a correlation between network packet loss and stereoscopic 3D video quality and was tuned according to extensive subjective testing results. Performance of eNVQM is studied in comparison with two state-of-the-art objective video quality metrics: structural similarity index (SSIM) and video quality metric (VQM).

A control approach is proposed in this study that controls the growth of a spatially growing mixing layer in an open loop. Due to the similarity of the mixing layer dynamics in the temporal and spatial domains, the control is exercised in the temporal domain that leads to optimization of the layer in the spatial domain. The proportional-integral-derivative (PID) control in the temporal domain uses Navier–Stokes equations as the plant model. Apart from being prohibitively expensive, control in the spatial domain presents convective time delay problems. These barriers are circumvented by solving the control problem in the temporal domain very rapidly, based on a given set point in the linear regime. Once the set point in the temporal domain is reached, the corresponding initial conditions in the temporal domain are mapped to inflow boundary conditions in the spatial domain. With these mapped inflow boundary conditions in the spatial domain, the spatial development of the mixing layer is followed, which confirms the efficacy of control in the spatial domain. The present control methodology offers a new paradigm for control of the spatially growing mixing layer.

Studying the topology of cerebral microvessels has been shown to be essential for understanding the mechanisms underlying neurovascular coupling and brain microphysiology. One can derive topological models of these microvessels after labeling them based on their raw acquisitions from two-photon microscopy (TPM). However, adequate 3D mapping of cerebral microvasculature from TPM remains difficult due to the uneven intensities and shadowing effects. In this paper, we present a novel 2D/3D skeletonization solution to generate topological graph models of microvessels regardless of the quality of their binary maps. Our scheme first constructs a random initial graph encapsulated within the boundary of a binary mask. The vertices of the initial model are then iteratively contracted toward the centerline of microvessels by local connectivity-encoded gravitational forces. At each iteration, the model is decimated through vertices clustering and connectivity surgery processes. Lastly, a refinement algorithm is applied to convert the final decimated model into a curve skeleton. Synthetic angiograms and real TPM datasets are used for evaluation. By comparing against other efficient graphing schemes, we demonstrate that our solution performs better when applied to extract topological information from cerebral microvessel labels.

view Abstract Citations (66) References (37) Co-Reads Similar Papers Volume Content Graphics Metrics Export Citation NASA/ADS Velocity Fields around Rich Clusters of Galaxies Villumsen, J. V. ; Davis, M. Abstract The authors study the nature of the velocity field around large clusters in Ω = 1 cosmological N-body simulations that have initial conditions which produce large-scale structure reasonably consistent with observations. The purpose is to test the accuracy of the spherical infall models commonly used to measure the mass of the Virgo supercluster and to characterize the nature of the deviations from simple spherical infall. The use of a spherical model for the Virgocentric flow as a measure of Ω is shown to be subject to large systematic and random errors. A much better test is to use a local criterion, noting that local peculiar velocity tracks the direction and amplitude of the local peculiar gravitational force extremely well. Publication: The Astrophysical Journal Pub Date: September 1986 DOI: 10.1086/164521 Bibcode: 1986ApJ...308..499V Keywords: Computational Astrophysics; Galactic Clusters; Many Body Problem; Velocity Distribution; Boundary Value Problems; Cosmology; Gravitational Effects; Mass Distribution; Virgo Galactic Cluster; Astrophysics; COSMOLOGY; GALAXIES: CLUSTERING; NUMERICAL METHODS full text sources ADS | data products SIMBAD (2)

The key to content-aware warping and cropping is adapting data to fit displays with various aspect ratios while preserving visually salient contents. Most previous studies achieve this objective by cropping insignificant contents near frame boundaries and consistently resizing frames through an optimization technique with various preservation constraints and fixed boundary conditions. These strategies significantly improve retargeting quality. However, warping under fixed boundary conditions may bound/limit the preservation of visually salient contents. Moreover, dynamic frame cropping and frame alignment may result in unnatural object/camera motions. In this paper, a floating boundary with volumetric warping and object-aware cropping is proposed to address these problems. In the proposed scheme, visually salient objects in the space-time domain are deformed as rigidly and as consistently as possible using information from matched objects and content-aware boundary constraints. The content-aware boundary constraints can retain visually salient contents in a fixed region with a desired resolution and aspect ratio, called critical region, during warping. Volumetric cropping with the fixed critical region is then performed to adjust stereoscopic videos to the desired aspect ratios. The strategies of warping and cropping using floating boundaries and spatiotemporal constraints enable our method to consistently preserve the temporal motions and spatial shapes of visually salient volumetric objects in the left and right videos as much as possible, thus leading to good content-aware retargeting. In addition, by considering shape, motion, and disparity preservation, the proposed scheme can be applied to various media, including images, stereoscopic images, videos, and stereoscopic videos. Qualitative and quantitative analyses of stereoscopic videos with diverse camera and considerable motions demonstrate a clear superiority of the proposed method over related methods in terms of retargeting quality.

Video sequences contain rich dynamic patterns, such as dynamic texture patterns that exhibit stationarity in the temporal domain, and action patterns that are non-stationary in either spatial or temporal domain. We show that an energy-based spatial-temporal generative ConvNet can be used to model and synthesize dynamic patterns. The model defines a probability distribution on the video sequence, and the log probability is defined by a spatial-temporal ConvNet that consists of multiple layers of spatial-temporal filters to capture spatial-temporal patterns of different scales. The model can be learned from the training video sequences by an "analysis by synthesis" learning algorithm that iterates the following two steps. Step 1 synthesizes video sequences from the currently learned model. Step 2 then updates the model parameters based on the difference between the synthesized video sequences and the observed training sequences. We show that the learning algorithm can synthesize realistic dynamic patterns. We also show that it is possible to learn the model from incomplete training sequences with either occluded pixels or missing frames, so that model learning and pattern completion can be accomplished simultaneously.

Image enhancement using image fusion is very important for many applications. Image fusion is performed in spatial domain or in transform domain. Weighted averaging-based image fusion is achieved in spatial domain. The fused image using this method is a low-contrast and blurriness image. The quality of the fused image in transform domain is better than fused image in spatial domain. The standard Discrete Wavelet Transform (DWT) based fusion is performed in transform domain and it produces better result compared with the weighted averaging-based fusion. However, the fused image using DWT based fusion lacks spatial details. In this paper, a simple image fusion is proposed in order to enhance the quality of the fused image using weighted averaging or DWT based image fusion for visible-infrared images. In nature, infrared image is a blurred image, so the convolution process is performed between the input infrared image and the proposed sharpen filter. The output is an image with highlighting edges and fine details. Using weighted averaging or DWT based image fusion to fuse the visible image and the enhanced infrared image to obtain the final image. The experimental results showed that the proposed fusion method produces better results than the standard fusion methods.

In this paper, we present a novel stereoscopic video quality assessment method based on 3D-DCT transform. In our approach, similar blocks from left and right views of stereoscopic video frames are found by block-matching, grouped into 3D stack and then analyzed by 3D-DCT. Comparison between reference and distorted images are made in terms of MSE calculated within the 3D-DCT domain and modified to reflect the contrast sensitive function and luminance masking. We validate our quality assessment method using test videos annotated with results from subjective tests. The results show that the proposed algorithm outperforms current popular metrics over a wide range of distortion levels.

Factor analysis in both spatial and temporal domains of color blooming artifacts in ultrasound investigations utilizing contrast agents