• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.294-297
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• 2009

Multi-view video consists of a set of multiple video sequences from multiple viewpoints or view directions in the same scene. It contains extremely a large amount of data and some extra information to be stored or transmitted to the user. This paper presents inter-view correlations among video objects and the background to reduce the prediction complexity while achieving a high coding efficiency in multi-view video coding. Our proposed algorism is based on object-based segmentation scheme that utilizes video object information obtained from the coded base view. This set of data help us to predict disparity vectors and motion vectors in enhancement views by employing object registration, which leads to high compression and low-complexity coding scheme for enhancement views. An experimental results show that the superiority can provide an improvement of PSNR gain 2.5.3 dB compared to the simulcast.

• The Journal of the Korea Contents Association
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• v.14 no.4
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• pp.9-18
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• 2014

Recently, many researches have been focused on multi-view video applications and services such as wireless video surveillance networks, wireless video sensor networks and wireless mobile video. In multi-view video signal processing, to exploit the strong correlation between images acquired by different cameras plays great role in developing a core technique of multi-view video coding. This paper proposes an adaptive multi-view video interpolation technique which is applicable for multi-view distributed video coding without requiring any cooperation amongst the cameras. The proposed algorithm estimates the non-linear moving blocks and employs disparity compensated view prediction, and then fills in the unreliable blocks. Through computer simulations, it is shown that the proposed method outperforms the conventional methods.

• Journal of Broadcast Engineering
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• v.15 no.6
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• pp.768-782
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• 2010

Because of the different shooting position between multi-view cameras and the imperfect camera calibration, Illumination mismatches of multi-view video can happen. This variation can bring about the performance decrease of multi-view video coding(MVC) algorithm. A histogram matching algorithm can be applied to recompensate these inconsistencies in a prefiltering step. Once all camera frames of a multi-view sequence are adjusted to a predefined reference through the histogram matching, the coding efficiency of MVC is improved. However the histogram distribution can be different not only between neighboring views but also between sequential views on account of movements of camera angle and some objects, especially human. Therefore the histogram matching algorithm which references all frames in chose view is not appropriate for compensating the illumination differences of these sequence. Thus we propose new algorithms both the image classification algorithm which is applied two criteria to improve the correlation between inter-view frames and the histogram matching which references and matches with a group of pictures(GOP) as a unit to advance the correlation between successive frames. Experimental results show that the compression ratio for the proposed algorithm is improved comparing with the conventional algorithms.

• Journal of Broadcast Engineering
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• v.22 no.3
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• pp.405-408
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• 2017

Based on the fact that high similarities exist between viewpoints of multi-view images, MV-HEVC achieves high encoding efficiency by performing conventional temporal direction prediction in a single viewpoint as well as inter-view prediction between viewpoints. In this paper, we propose to integrate SHVC and MVC (Multi-view Video Coding) to implement scalable multi-view video encoder using HEVC as a base layer. According to experimental results, it is verified that the BD-PSNR improvement reaches up to 1.5dB while reducing the BD-Bitrate by around 50~60%.

• Journal of Broadcast Engineering
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• v.11 no.4 s.33
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• pp.407-419
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• 2006

In this paper, an adaptive illumination change compensation method is proposed for multi-view video coding. In multi-view video, an illumination change can occur due to physically imperfect camera calibration, each different camera position and direction, and so on. These characteristics can cause a performance decrease in the multi-view video coding that uses an inter-view prediction by referring to the pictures obtained from the neighboring views. By using the proposed method, a compression ratio of the proposed method in the multi-view video coding is increased, and finally $0.1{\sim}0.6dB$ PSNR(Peak Signal-to-Noise Ratio) improvement was obtained compared with the case of not using the proposed method.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.8
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• pp.245-249
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• 2013

In this paper, we propose two rate control algorithms for multi-view extension of HEVC with two rate control algorithms adopted in HEVC and analyze the multi-view rate control performance. The proposed multi-view rate controls are designed on HEVC-based multi-view video coding (MV-HEVC) platform with consideration of high-level syntax, inter-view prediction, etc. not only for the base view but also for the extended views using the rate control algorithms based on URQ (Unified Rate-Quantization) and R-lambda model adopted in HEVC. The proposed multi-view rate controls also contain view-wise target bit allocation for providing the compatibility to the base view. By allocating the target bitrates for each view, the proposed multi-view rate control based on URQ model achieved about 1.83% of average bitrate accuracy and 1.73dB of average PSNR degradation. In addition, about 2.97% of average bitrate accuracy and 0.31dB of average PSNR degradation are achieved with the proposed multi-view rate control based on R-lambda model.

• Journal of Korea Multimedia Society
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• v.15 no.9
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• pp.1093-1101
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• 2012

Multi-view video is obtained by capturing one three-dimensional scene with many cameras at different positions. Multi-view video coding exploits inter-view correlations among pictures of neighboring views and temporal correlations among pictures of the same view. Multi-view video coding which uses many cameras requires a method to reduce the computational complexity. In this paper, we proposed an efficient prediction structure to improve performance of multi-view video coding. The proposed prediction structure exploits an average distance between the current picture and its reference pictures. The proposed prediction structure divides every GOP into several small groups to decide the maximum index of hierarchical B layer and the number of pictures of each B layer. Experimental results show that the proposed prediction structure shows good performance in image quality and bit-rates. When compared to the performance of hierarchical B pictures of Fraunhofer-HHI, the proposed prediction structure achieved 0.07~0.13 (dB) of PSNR gain and was down by 6.5(Kbps) in bitrate.

• Journal of Broadcast Engineering
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• v.10 no.3
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• pp.321-327
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• 2005

A MVC (Multi-view Video Coding) method, which uses both an illumination change-adaptive ME (Motion Estimation)/DC (Motion Compensation) and a 2D (Dimensional) direct mode, is proposed. Firstly, a new SAD (Sum of Absolute Difference) measure for ME/MC is proposed to compensate the Luma pixel value changes for spatio-temporal motion vector prediction. Illumination change-adaptive (ICA) ME/MC uses the new SAD to improve both MV (Motion Vector) accuracy and bit saving. Secondly, The proposed 2D direct mode that can be used in inter-view prediction is an extended version of the temporal direct mode in MPEG-4 AVC. The proposed MVC method obtains approximately 0.8dB PSNR (Peak Signal-to-Noise Ratio) increment compared with the MPEG-4 AVC simulcast coding.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.6
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• pp.127-136
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• 2010

In multi-view video, illumination disharmony between neighboring views can occur on account of different location of each camera and imperfect camera calibration, and so on. Such discrepancy can be the cause of the performance decrease of multi-view video coding by mismatch of inter-view prediction which refer to the pictures obtained from the neighboring views at the same time. In this paper, we propose an efficient histogram-based prefiltering algorithm to compensate mismatches between the luminance and chrominance components in multi-view video for improving its coding efficiency. To compensate illumination variation efficiently, all camera frames of a multi-view sequence are adjusted to a predefined reference through the histogram matching. A Cosited filter that is used for chroma subsampling in many video encoding schemes is applied to each color component prior to histogram matching to improve its performance. The histogram matching is carried out in the RGB color space after color space converting from YCbCr color space. The effective color conversion skill that has respect to direction of edge and range of pixel value in an image is employed in the process. Experimental results show that the compression ratio for the proposed algorithm is improved comparing with other methods.

• Journal of Broadcast Engineering
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• v.11 no.4 s.33
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• pp.386-395
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• 2006

Multi-view video coding technology demands the very high efficient coding technologies, because it has to encode a number of video sequences which are achieved from a number of video cameras. For this purpose, multi-view video coding introduces the inter-view prediction scheme between different views, but it shows a limitation of coding performance enhancement by adopting only new prediction method. Accordingly, we are going to achieve the more coding performance by enhancing dequantizer perfermance. Multi-view video coding is implemented basically based on H.264/AVC and uses the same quantization/de-quantization method as H.264/AVC does. The conventional quantizer and dequantizer is designed with the assumption that input residual signal follows the Laplacian PDF. However, it doesn't follow the fixed PDF type always. This mismatch between assumption and real data causes degradation of coding performance. To solve this problem, we propose the efficient de-quantization method based on quantized coefficients distribution at decoder without extra information. The extensive simulation results show that the proposed algorithm produces maximum $1.5\;dB{\sim}0.6\;dB$ at high bitrate compared with that of conventional method.