• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2006.11a
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• pp.257-260
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• 2006

In Video streaming environment, we must consider terminal and network characteristics, such as display resolution, frame rate, computational resource, network bandwidth, etc. The JVT (Joint Video Team) by ISO/IEC MPEG and ITU-TVCEG is currently standardizing Scalable Video Coding (SVC). This can represent video bitstreams in different sealable layers for flexible adaptation to terminal and network characteristics. This characteristic is very useful in video streaming applications. One fully scalable video can be extracted with specific target spatial resolution, temporal frame rate and quality level to match the requirements of terminals and networks. Besides, the extraction process is fast and consumes little computational resource, so it is possible to extract the partial video bitstream online to accommodate with changing network conditions etc. With all the advantages of SVC, we design and implement a network-adaptive SVC streaming system with an SVC extractor and a streamer to extract appropriate amounts of bitstreams to meet the required target bitrates and spatial resolutions. The proposed SVC extraction is designed to allow for flexible switching from layer to layer in SVC bitstreams online to cope with the change in network bandwidth. The extraction is made in every GOP unit. We present the implementation of our SVC streaming system with experimental results.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.8
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• pp.4077-4091
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• 2017

This paper presents the design of a broadcasting scenario and system for an 8K-resolution content. Due to an 8K content is four times larger than the 4K content in terms of size, many technologies such as content acquisition, video coding, and transmission are required to deal with it. Therefore, high-quality video and audio for 8K (ultra-high definition television) service is not possible to be transmitted only using the current terrestrial broadcasting system. The proposed broadcasting system divides the 8K content into four 4K contents by area, and each area is hierarchically encoded by Scalable High-efficiency Video Coding (SHVC) into three layers: L0, L1, and L2. Every part of the 8K video content divided into areas and hierarchy is independently treated. These parts are transmitted over heterogeneous networks such as digital broadcasting and broadband networks after going through several processes of generating signal messages, encapsulation, and packetization based on MPEG media transport. We propose three methods of generating streams at the sending entity to merge the divided streams into the original content at the receiving entity. First, we design the composition information, which defines the presentation structure for displays. Second, a descriptor for content synchronization is included in the signal message. Finally, we define the rules for generating "packet_id" among the packet header fields and design the transmission scheduler to acquire the divided streams quickly. We implement the 8K broadcasting system by adapting the proposed methods and show that the 8K-resolution contents are stably received and serviced with a low delay.

• Journal of Broadcast Engineering
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• v.24 no.3
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• pp.401-410
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• 2019

In this paper, we propose a reference picture generation method for Inter-layer prediction based deep learning to improve the SHVC coding performance. A description will be given of a structure for performing filtering using a VDSR network on a DCT-IF based upsampled picture to generate a new reference picture and a training method for generating a reference picture between SHVC Inter-layer. The proposed method is implemented based on SHM 12.0. In order to evaluate the performance, we compare the method of generating Inter-layer predictor by applying dictionary learning. As a result, the coding performance of the enhancement layer showed a bitrate reduction of up to 13.14% compared to the method using dictionary learning, a bitrate reduction of up to 15.39% compared to SHM, and a bitrate reduction of 6.46% on average.