67 research outputs found
Open-Source Telemedicine Platform for Wireless Medical Video Communication
An m-health system for real-time wireless communication of medical video based on open-source software is presented. The objective is to deliver a low-cost telemedicine platform which will allow for reliable remote diagnosis m-health applications such as emergency incidents, mass population screening, and medical education purposes. The performance of the proposed system is demonstrated using five atherosclerotic plaque ultrasound videos. The videos are encoded at the clinically acquired resolution, in addition to lower, QCIF, and CIF resolutions, at different bitrates, and four different encoding structures. Commercially available wireless local area network (WLAN) and 3.5G high-speed packet access (HSPA) wireless channels are used to validate the developed platform. Objective video quality assessment is based on PSNR ratings, following calibration using the variable frame delay (VFD) algorithm that removes temporal mismatch between original and received videos. Clinical evaluation is based on atherosclerotic plaque ultrasound video assessment protocol. Experimental results show that adequate diagnostic quality wireless medical video communications are realized using the designed telemedicine platform. HSPA cellular networks provide for ultrasound video transmission at the acquired resolution, while VFD algorithm utilization bridges objective and subjective ratings
Information fusion based techniques for HEVC
Aiming at the conflict circumstances of multi-parameter H.265/HEVC encoder system, the present paper introduces the analysis of many optimizations\u27 set in order to improve the trade-off between quality, performance and power consumption for different reliable and accurate applications. This method is based on the Pareto optimization and has been tested with different resolutions on real-time encoders
Mode decision for the H.264/AVC video coding standard
H.264/AVC video coding standard gives us a very promising future for the
field of video broadcasting and communication because of its high coding
efficiency compared with other older video coding standards. However, high
coding efficiency also carries high computational complexity. Fast motion
estimation and fast mode decision are two very useful techniques which can
significantly reduce computational complexity.
This thesis focuses on the field of fast mode decision. The goal of this thesis is
that for very similar RD performance compared with H.264/AVC video coding
standard, we aim to find new fast mode decision techniques which can afford
significant time savings. [Continues.
Efficient compression of synthetic video
Streaming of on-line gaming video is a challenging problem because of the enormous
amounts of video data that need to be sent during game playing, especially within the
limitations of uplink capabilities. The encoding complexity is also a challenge because of
the time delay while on-line gamers are communicating.
The main goal of this research study is to propose an enhanced on-line game video
streaming system. First, the most common video coding techniques have been evaluated.
The evaluation study considers objective and subjective metrics. Three widespread video
coding techniques are selected and evaluated in the study; H.264, MPEG-4 Visual and VP-
8. Diverse types of video sequences were used with different frame rates and resolutions.
The effects of changing frame rate and resolution on compression efficiency and viewers‟
satisfaction are also presented. Results showed that the compression process and perceptual
satisfaction are severely affected by the nature of the compressed sequence. As a result,
H.264 showed higher compression efficiency for synthetic sequences and outperformed
other codecs in the subjective evaluation tests.
Second, a fast inter prediction technique to speed up the encoding process of H.264 has
been devised. The on-line game streaming service is a real time application, thus,
compression complexity significantly affects the whole process of on-line streaming. H.264
has been recommended for synthetic video coding by our results gained in codecs
comparative studies. However, it still suffers from high encoding complexity; thus a low
complexity coding algorithm is presented as fast inter coding model with reference
management technique. The proposed algorithm was compared to a state of the art method,
the results showing better achievement in time and bit rate reduction with negligible loss of
fidelity.
Third, recommendations on tradeoff between frame rates and resolution within given uplink
capabilities are provided for H.264 video coding. The recommended tradeoffs are offered as a result of extensive experiments using Double Stimulus Impairment Scale (DSIS)
subjective evaluation metric. Experiments showed that viewers‟ satisfaction is profoundly
affected by varying frame rates and resolutions. In addition, increasing frame rate or frame
resolution does not always guarantee improved increments of perceptual quality. As a
result, tradeoffs are recommended to compromise between frame rate and resolution within
a given bit rate to guarantee the highest user satisfaction.
For system completeness and to facilitate the implementation of the proposed techniques,
an efficient game video streaming management system is proposed.
Compared to existing on-line live video service systems for games, the proposed system
provides improved coding efficiency, complexity reduction and better user satisfaction
Pre-processing techniques to improve HEVC subjective quality
Nowadays, HEVC is the cutting edge encoding standard being the most efficient solution for transmission of video content. In this paper a subjective quality improvement based on pre-processing algorithms for homogeneous and chaotic regions detection is proposed and evaluated for low bit-rate applications at high resolutions. This goal is achieved by means of a texture classification applied to the input frames. Furthermore, these calculations help also reduce the complexity of the HEVC encoder. Therefore both the subjective quality and the HEVC performance are improved
High capacity data embedding schemes for digital media
High capacity image data hiding methods and robust high capacity digital audio watermarking algorithms are studied in this thesis. The main results of this work are the development of novel algorithms with state-of-the-art performance, high capacity and transparency for image data hiding and robustness, high capacity and low distortion for audio watermarking.En esta tesis se estudian y proponen diversos métodos de data hiding de imágenes y watermarking de audio de alta capacidad. Los principales resultados de este trabajo consisten en la publicación de varios algoritmos novedosos con rendimiento a la altura de los mejores métodos del estado del arte, alta capacidad y transparencia, en el caso de data hiding de imágenes, y robustez, alta capacidad y baja distorsión para el watermarking de audio.En aquesta tesi s'estudien i es proposen diversos mètodes de data hiding d'imatges i watermarking d'à udio d'alta capacitat. Els resultats principals d'aquest treball consisteixen en la publicació de diversos algorismes nous amb rendiment a l'alçada dels millors mètodes de l'estat de l'art, alta capacitat i transparència, en el cas de data hiding d'imatges, i robustesa, alta capacitat i baixa distorsió per al watermarking d'à udio.Societat de la informació i el coneixemen
No-reference video quality estimation based on machine learning for passive gaming video streaming applications
Recent years have seen increasing growth and popularity of gaming services, both interactive and passive. While interactive gaming video streaming applications have received much attention, passive gaming video streaming, in-spite of its huge success and growth in recent years, has seen much less interest from the research community. For the continued growth of such services in the future, it is imperative that the end user gaming quality of experience (QoE) is estimated so that it can be controlled and maximized to ensure user acceptance. Previous quality assessment studies have shown not so satisfactory performance of existing No-reference (NR) video quality assessment (VQA) metrics. Also, due to the inherent nature and different requirements of gaming video streaming applications, as well as the fact that gaming videos are perceived differently from non-gaming content (as they are usually computer generated and contain artificial/synthetic content), there is a need for application specific light-weight, no-reference gaming video quality prediction models. In this paper, we present two NR machine learning based quality estimation models for gaming video streaming, NR-GVSQI and NR-GVSQE, using NR features such as bitrate, resolution, blockiness, etc. We evaluate their performance on different gaming video datasets and show that the proposed models outperform the current state-of-the-art no-reference metrics, while also reaching a prediction accuracy comparable to the best known full reference metric
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