• Journal of the Semiconductor & Display Technology
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• v.12 no.1
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• pp.35-39
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• 2013

H.264/AVC is an authoritative international video coding standard which shows code and efficiency more improved than the existing video standards. Above all, the parameter block mode of H.264/AVC significantly contributes much to high compression efficiency. However, as the occasion demands, users tend to pass while overlooking the part that can produce a little higher compression efficiency. We, taking notice of this point, are designed to bring in much higher compression efficiency by gathering up the overlooked parts. This paper suggests the algorithm that produces efficient performance improvement by using the histogram of luminance in the pixel unit (Macroblock) of respective prediction block and applying specific thresholds. The experimental results proves that the technique proposed by this paper increases the compression efficiency of the existing H.264/AVC algorithm by 0.4% without any increase in the whole encoding time and PSNR complexity.

• The KIPS Transactions:PartB
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• v.10B no.1
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• pp.95-102
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• 2003

In surveillance video system, there are many classes of images and some spatial regions are more important than other regions. The conventional compression method in this system have been compressed there full frames without classfying them depend on their important parts. To improve the accuracy of the image coding and deliver effective compression for the surveillance video system, it was necessary to separate the regions according to their importance. In this paper, we propose a new effective surveillance video image compression method. The proposed scheme defines importance based three-level region of interest block in a frame, such as background, motion object block, and the feature object block. A captured video image frame can be separated to these three different levels of block regions. And depends on the priority, each block can be modified and compressed in different resolution, compression ratio and qualify factor. Therefore, in surveillance video system, this algorithm not only reduces the image processing time and space, but also guarantees the Important image data in high quality to acquire the system's goal.

• Proceedings of the IEEK Conference
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• 2005.11a
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• pp.639-642
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• 2005

Motion Estimation(ME) is an important part of video compression, because it requires a large amount of computation. Half-pixel and quarter-pixel motion estimation allows high video compression rates but it also has high computation complexity. In this paper we suggest a new and efficient motion estimation algorithm for half-pixel and quarter-pixel motion estimation using SAD values. In the method, an integer-pixel motion vector is found and then only three neighboring points of the integer-pixel motion vector is evaluated to find the half-pixel motion vector. The quarter-pixel motion vector is also found by using a similar method. Experimental results of our method shows 20% reduction in computation time, when compared with those of a conventional method, while producing same quality motion vectors.

• 한국정보디스플레이학회:학술대회논문집
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• 2007.08b
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• pp.1508-1511
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• 2007

This paper introduces a new texture prediction for MVC( Multi-view Video Coding) which is currently being developed as an extension of the ITU-T Recommendation H.264 | ISO/IEC International Standard ISO/IEC 14496-10 AVC (Advanced Video Coding) [1]. The MVC's prcimary target is 3D video compression for 3D display system, thus, key technology compared to 2D video compression is reducing inter-view correlation. It is noticed, however, that the current JMVM [2] does not effectively eliminate inter-view correlation so that there is still a room to improve coding efficiency. The proposed method utilizes similarity of interview residual signal and can provide an additional coding gain. It is claimed that up to 0.2dB PSNR gain with 1.4% bit-rate saving is obtained for three multi-view test sequences.

• Journal of Korea Society of Digital Industry and Information Management
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• v.12 no.4
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• pp.115-121
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• 2016

Recently, it has become an important problem to extract semantic objects from videos, which are useful for improving the performance of video compression and video retrieval. In this thesis, an automatic extraction method of moving objects of interest in video is suggested. We define that an moving object of interest should be relatively large in a frame image and should occur frequently in a scene. The moving object of interest should have different motion from camera motion. Moving object of interest are determined through spatial continuity by the AMOS method and moving histogram. Through experiments with diverse scenes, we found that the proposed method extracted almost all of the objects of interest selected by the user but its precision was 69% because of over-extraction.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.2
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• pp.427-434
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• 2018

Video services have been widely generalized thanks to the progress in compression streaming technologies. In spite of the innate difficulties in guaranteeing quality of service(QoS) of the Internet, the quality of service that is experienced by users have been improved considerably with overall bandwidth growth over the Internet and new compression and streaming technologies. For further sophisticated management scheme from the current homogeneous one, it should consider the characteristics of video contents. This paper investigates that the Quality of Experience(: QoE) for video services can vary according to the characteristics of video contents for the same compression method and transmission environments. It is expected that this result contributes to establish a new and advanced scheme to manage QoE for video services over the Internet.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.2
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• pp.435-449
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• 2023

The state-of-the-art video-based point cloud compression(V-PCC) has a high efficiency of compressing 3D point cloud by projecting points onto 2D images. These images are then padded and compressed by High-Efficiency Video Coding(HEVC). Pixels in padded 2D images are classified into three groups including origin pixels, padded pixels and unoccupied pixels. Origin pixels are generated from projection of 3D point cloud. Padded pixels and unoccupied pixels are generated by copying values from origin pixels during image padding. For padded pixels, they are reconstructed to 3D space during geometry reconstruction as well as origin pixels. For unoccupied pixels, they are not reconstructed. The rate distortion optimization(RDO) used in HEVC is mainly aimed at keeping the balance between video distortion and video bitrates. However, traditional RDO is unreliable for padded pixels and unoccupied pixels, which leads to significant waste of bits in geometry reconstruction. In this paper, we propose a new RDO scheme which takes 3D-Distortion into account instead of traditional video distortion for padded pixels and unoccupied pixels. Firstly, these pixels are classified based on the occupancy map. Secondly, different strategies are applied to these pixels to calculate their 3D-Distortions. Finally, the obtained 3D-Distortions replace the sum square error(SSE) during the full RDO process in intra prediction and inter prediction. The proposed method is applied to geometry frames. Experimental results show that the proposed algorithm achieves an average of 31.41% and 6.14% bitrate saving for D1 metric in Random Access setting and All Intra setting on geometry videos compared with V-PCC anchor.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.650-652
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• 2022

Frame rate up-conversion (FRUC) algorithm is an image interpolation technology that improves the frame rate of moving pictures. This solves problems such as screen shake or blurry motion caused by low frame rate video in high-definition digital video systems, and provides viewers with a more free and smooth visual experience. In this paper, we propose a video compression technique using deep learning-based FRUC algorithm. The proposed method compresses and transmits after excluding some images from the original video, and uses a deep learning-based interpolation method in the decoding process to restore the excluded images, thereby compressing them with high efficiency. In the experiment, the compression performance was evaluated using the decoded image and the image restored by the FRUC algorithm after encoding the video by skipping 1 or 3 pages. When 1 and 3 sheets were excluded, the average BD-rate decreased by 81.22% and 27.80%. The reason that excluding three images has lower encoding efficiency than excluding one is because the PSNR of the image reconstructed by the FRUC method is low.

• Journal of the Korea Computer Industry Society
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• v.3 no.3
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• pp.283-294
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• 2002

Now is the time for web-based video e-mail system because of world wide use of internet. But video data is so large, then data compression is much needed for transmission by web. In this paper, my colleagues and I implement full motion video e-mail system using MPEG-4, the international standards for audio-visual data. This video e-mail system is made of web-based active-X control, so easily accessible by web, and applies real-time audio-video compression. It's possible for everyone to send video e-mail for free to everywhere in the world if this system is used. The main application areas of this system are multimedia mailing service, web-based video advertisement, remote education, remote medical service and shopping mall construction, etc.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.6
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• pp.1104-1114
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• 2007

Digital video compression technique has played an important role that enables efficient transmission and storage of multimedia data where bandwidth and storage space are limited. The new video coding standard, H.264/AVC, developed by Joint Video Team(JVT) significantly outperforms previous standards in compression performance. Especially, variable length code(VLC) plays a crucial pun in video and image compression applications. H.264/AVC standard adopted Context-based Adaptive Variable Length Coding(CAVLC) as the entropy coding method. CAVLC of H.264/AVC requires a large number of the memory accesses. This is a serious problem for applications such as DMB and video phone service because of the considerable amount of power that is consumed in accessing the memory. In order to overcome this problem in this paper, we propose a variable length technique that implements memory-free coeff_token, level, and run_before decoding based on arithmetic operations and using only 70% of the required memory at total_zero variable length decoding.