• Journal of Broadcast Engineering
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• v.24 no.1
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• pp.132-141
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• 2019

The necessity of transmitting video data over a narrow-bandwidth exists steadily despite that video service over broadband is common. In this paper, we propose a scalable video coding framework for low-resolution video transmission over a very narrow-bandwidth network by super-resolution of decoded frames of a base layer using a convolutional neural network based super resolution technique to improve the coding efficiency by using it as a prediction for the enhancement layer. In contrast to the conventional scalable high efficiency video coding (SHVC) standard, in which upscaling is performed with a fixed filter, we propose a scalable video coding framework that replaces the existing fixed up-scaling filter by using the trained convolutional neural network for super-resolution. For this, we proposed a neural network structure with skip connection and residual learning technique and trained it according to the application scenario of the video coding framework. For the application scenario where a video whose resolution is $352{\times}288$ and frame rate is 8fps is encoded at 110kbps, the quality of the proposed scalable video coding framework is higher than that of the SHVC framework.

• Journal of the Institute of Electronics and Information Engineers
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• v.49 no.9
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• pp.92-103
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• 2012

In this paper, we discuss and propose a new algorithm of coding technique for scalably servicing holographic video in various decoding environment. The proposed algorithm consists of the hologram-based resolution scalable coding (HRS) and the light source-based SNR scalable coding (LSS). They are classified by the method generating and capturing hologram. HRS is a scalable coding technique for the optically captured hologram and LSS is one for the light source before generating hologram. HRS can provide the scalable service of 8 steps with the compression ratio from 1:1 to 100:1 for a $1,024{\times}1,024$ hologram. LSS can also provide the various service depending on the number of the light source division using lossless compression. The proposed techniques showed the scalable holographic video service according to the display with the various resolutions, computational power of the receiving equipment, and the network bandwidth.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.195-197
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• 2005

In the scalable extension of H.264/AVC, spatial scalability is provided residual information as encoding layered spatial resolution between layers. We use the inter-layer prediction to remove this redundancy. In the inter-layer prediction, as the prediction we can use the signal that is the upsampled signal of the lower resolution layer. In this case, coding efficiency can be different from optimal prediction by kinds of interpolation filter. This paper indicates technique to choose the interpolation filter and to enhance coding efficiency for finding more correct prediction in intra macroblock.

• Proceedings of the IEEK Conference
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• 2002.07a
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• pp.50-53
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• 2002

There are increasing needs to deliver the multimedia streaming over heterogeneous networks. When considering network environments and equipment accessed by user, delivery of video streaming must be scalable. There are many kinds of scalable video coding: spatial, temporal, SNR, and hybrid. The SNR scalable and spatial resolution, but different SNR quality with respect to layers. The 1-layer SNR scalable encoder produces SNR scalable video streams with ease. But, there is drift problem. Modified 1-layer approach does not have this problem but coding inefficiency, and is not MPEG-compliant. The present MPEG-compliant 2-layer encoder comes out to reduce coding rate. But it still use only base layer to encode whole layer. In this paper, we propose adaptive MPEG-compliant 2-layer encoder. Using linear combination algorithm, encoder use 1 motion vector to encode the sequences efficiently. By dong this, we can achieve the coding efficiency of SNR scalable coding.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.10
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• pp.4108-4125
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• 2015

This paper presents a scalable coding method for depth images by considering the quality of synthesized images in virtual views. First, we design a new edge detection algorithm that is based on calculating the depth difference between two neighboring pixels within the depth map. By choosing different thresholds, this algorithm generates a scalable bit stream that puts larger depth differences in front, followed by smaller depth differences. A scalable scheme is also designed for coding depth pixels through a layered sampling structure. At the receiver side, the full-resolution depth image is reconstructed from the received bits by solving a partial-differential-equation (PDE). Experimental results show that the proposed method improves the rate-distortion performance of synthesized images at virtual views and achieves better visual quality.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.189-191
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• 2005

In the scalable extension of H.264/AVC, the codec is based on a layered approach to enable spatial scalability. In each layer, the basic concepts of motion compensated prediction and intra prediction are employed as in standard H.264/AVC. Additionally inter-layer prediction algorithm between successive spatial layers is applied to remove redundancy. In the inter-layer prediction, as the prediction we can use the signal that is the upsampled signal of the lower resolution layer. In this case, coding efficiency can be variable as the kinds of interpolation filter. In this paper, we investigate the approach to select the interpolation filter for residual signal in order to optimal prediction.

• Proceedings of the KIEE Conference
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• 1993.11a
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• pp.342-345
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• 1993

In this paper, we study the structure of the hierarchical coding method of video signal which can contain the multi resolution video signals. To preserve the compatibility with the conventional coding methods. we accomplished a scalable structure using the subband coding, maintaining enoughly the international coding structure. The proposed scheme showed the low PSNR, a little, when compared with the conventional scheme, but showed a good image quality perceptually and proved to have a advantage in the H/W implementation in a view of processing speed.

• ETRI Journal
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• v.28 no.2
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• pp.239-242
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• 2006

In this letter, we propose a new functionality to scalable video coding (SVC), that is, the support of multiple region of interests (ROIs) for heterogeneous display resolution. The main objective of SVC is to provide temporal, spatial, and quality scalability of an encoded bitstream. The ROI is an area that is semantically important to a particular user, especially users with heterogeneous display resolutions. Less transmission bandwidth is needed compared to when the entire region is transmitted/decoded and then sub-sampled or cropped. To support multiple ROIs in SVC, we adopt flexible macroblock ordering (FMO), a tool defined in H.264, and based on it, we propose a way to encode and, independently, decode ROIs. The proposed method is implemented on the joint scalable video model (JSVM) and its functionality verified.

• Journal of Broadcast Engineering
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• v.19 no.2
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• pp.174-183
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• 2014

This paper is to propose a scalable video coding scheme for adaptive digital hologram video service for various reconstruction environments. It uses both the light source information and digital hologram at both the sending side and the receiving side. It is a resolution-scalable coding method that scales the resolution, that is, the size of the reconstructed image. The method compresses the residual data for both the digital hologram and the light source information. For the digital hologram, a lossy compression method is used, while for the light source information, a lossless compression method is used. The experimental results showed that the proposed method is superior to the existing method in the image quality at the same compression ratio. Especially it showed better performance than the existing method as the compression ratio becomes higher.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.10
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• pp.118-128
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• 2015

Compressive sensing (CS) has to face with two challenges of computational complexity reconstruction and low coding efficiency. As a solution, this paper presents a novel spatially scalable Kronecker two layer compressive sensing framework which facilitates reconstruction up to three spatial resolutions as well as much improved CS coding performance. We propose a dual-resolution sensing matrix based on the quincunx sampling grid which is applied to the base layer. This sensing matrix can provide a fast-preview of low resolution image at encoder side which is utilized for predictive coding. The enhancement layer is encoded as the residual measurement between the acquired measurement and predicted measurement data. The low resolution reconstruction is obtained from the base layer only while the high resolution image is jointly reconstructed using both two layers. Experimental results validate that the proposed scheme outperforms both conventional single layer and previous multi-resolution schemes especially at high bitrate like 2.0 bpp by 5.75dB and 5.05dB PSNR gain on average, respectively.