Content-adaptive frame level rate control for video encoding using a perceptual video quality measure

2019 ◽  
Author(s):  
Tamar Shoham ◽  
Dror Gill ◽  
Sharon Carmel ◽  
Nikolay Terterov ◽  
Pavel Tiktov
Keyword(s):  
Rate Control ◽  
Video Quality ◽  
Quality Measure ◽  
Video Encoding ◽  
Perceptual Video Quality ◽  
Content Adaptive

PVQM – A perceptual video quality measure

2002 ◽  
Vol 17 (10) ◽  
pp. 781-798 ◽  
Author(s):  
A.P. Hekstra ◽  
J.G. Beerends ◽  
D. Ledermann ◽  
F.E. de Caluwe ◽  
S. Kohler ◽  
...  
Keyword(s):  
Video Quality ◽  
Quality Measure ◽  
Perceptual Video Quality

Adaptive Skipping Frame in TMN8 Rate Control

2012 ◽  
Vol 195-196 ◽  
pp. 998-1002
Author(s):  
Xiao Ping Huang ◽  
Ru Jun Cao ◽  
Peng Ying Wang
Keyword(s):  
Real Time ◽  
Rate Control ◽  
Video Quality ◽  
Video Encoding ◽  
Perceptual Quality ◽  
Computation Complexity ◽  
Low Bit Rate ◽  
Image Characteristic ◽  
Large Motion ◽  
Temporal And Spatial

The skipping frame algorithm in TMN8 rate control only depending on buffer state regardless of image characteristic, may skip important frames with large motion and, as a result, video quality seriously reduced. An adaptive skipping frame algorithm is proposed for low-bit rate real-time video encoding. The occurrence of frame skipping is jointly dependent on the temporal and spatial contents of the video, and achieves a balanced spatial and temporal quality to enhance the overall perceptual quality. Experimental results show that the proposed algorithm can achieve the better subjective and objective video quality than TMN8s algorithm, without introducing any computation complexity.

scholarly journals Content Dependent Representation Selection Model for Systems Based on MPEG DASH

Electronics ◽  
2021 ◽  
Vol 10 (15) ◽  
pp. 1843
Author(s):  
Jelena Vlaović ◽  
Snježana Rimac-Drlje ◽  
Drago Žagar
Keyword(s):  
Mathematical Model ◽  
Spatial Information ◽  
Relevant Literature ◽  
Video Quality ◽  
Similarity Index ◽  
Video Encoding ◽  
Adaptation Algorithm ◽  
Subjective Testing ◽  
Proposed Model ◽  
The Mathematical Model

A standard called MPEG Dynamic Adaptive Streaming over HTTP (MPEG DASH) ensures the interoperability between different streaming services and the highest possible video quality in changing network conditions. The solutions described in the available literature that focus on video segmentation are mostly proprietary, use a high amount of computational power, lack the methodology, model notation, information needed for reproduction, or do not consider the spatial and temporal activity of video sequences. This paper presents a new model for selecting optimal parameters and number of representations for video encoding and segmentation, based on a measure of the spatial and temporal activity of the video content. The model was developed for the H.264 encoder, using Structural Similarity Index Measure (SSIM) objective metrics as well as Spatial Information (SI) and Temporal Information (TI) as measures of video spatial and temporal activity. The methodology that we used to develop the mathematical model is also presented in detail so that it can be applied to adapt the mathematical model to another type of an encoder or a set of encoding parameters. The efficiency of the segmentation made by the proposed model was tested using the Basic Adaptation algorithm (BAA) and Segment Aware Rate Adaptation (SARA) algorithm as well as two different network scenarios. In comparison to the segmentation available in the relevant literature, the segmentation based on the proposed model obtains better SSIM values in 92% of cases and subjective testing showed that it achieves better results in 83.3% of cases.

scholarly journals Perceptual Video Quality Prediction Emphasizing Chroma Distortions

2021 ◽  
Vol 30 ◽  
pp. 1408-1422
Author(s):  
Li-Heng Chen ◽  
Christos G. Bampis ◽  
Zhi Li ◽  
Joel Sole ◽  
Alan C. Bovik
Keyword(s):  
Video Quality ◽  
Quality Prediction ◽  
Perceptual Video Quality

Perceptual video quality assessment for adaptive streaming encoding

2015 ◽  
Author(s):  
Estevao C. Monteiro ◽  
Ricardo E. P. Scholz ◽  
Carlos A. G. Ferraz ◽  
Tsang I. Ren ◽  
Roberto S. M. Barros
Keyword(s):  
Quality Assessment ◽  
Video Quality ◽  
Video Quality Assessment ◽  
Adaptive Streaming ◽  
Perceptual Video Quality

scholarly journals Video Cloud Services for Hospitals: Designing an End-to-End Cloud Service Platform for Medical Video Storage and Secure Access

10.2196/18139 ◽  
2020 ◽  
Vol 5 (1) ◽  
pp. e18139
Author(s):  
Piotr Pawałowski ◽  
Cezary Mazurek ◽  
Mikołaj Leszczuk ◽  
Jean-Marie Moureaux ◽  
Amine Chaabouni
Keyword(s):  
Video Quality ◽  
Cloud Service ◽  
Video Data ◽  
Cloud Services ◽  
Information And Communications Technology ◽  
Video Encoding ◽  
Rapid Expansion ◽  
Long Run ◽  
Generic Architecture ◽  
End To End

The amount of medical video data that has to be securely stored has been growing exponentially. This rapid expansion is mainly caused by the introduction of higher video resolution such as 4K and 8K to medical devices and the growing usage of telemedicine services, along with a general trend toward increasing transparency with respect to medical treatment, resulting in more and more medical procedures being recorded. Such video data, as medical data, must be maintained for many years, resulting in datasets at the exabytes scale that each hospital must be able to store in the future. Currently, hospitals do not have the required information and communications technology infrastructure to handle such large amounts of data in the long run. In this paper, we discuss the challenges and possible solutions to this problem. We propose a generic architecture for a holistic, end-to-end recording and storage platform for hospitals, define crucial components, and identify existing and future solutions to address all parts of the system. This paper focuses mostly on the recording part of the system by introducing the major challenges in the area of bioinformatics, with particular focus on three major areas: video encoding, video quality, and video metadata.

VBR rate control for perceptually consistent video quality

2008 ◽  
Vol 54 (4) ◽  
pp. 1912-1919 ◽  
Author(s):  
Bo Han ◽  
Bingfeng Zhou
Keyword(s):  
Rate Control ◽  
Video Quality
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