• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.25 no.7A
• /
• pp.994-1004
• /
• 2000

In this paper, bitstreams are composed of using H.263 for a moving picture coding in the band-limited and error-prone environment such as wireless environment. EREC sub-frames are implemented by applying the proposed EREC algorithm in order to be UEP for the real data parts of implemented bitstreams. Because those are able to do resynchronization with a block unit, propagation of the error can be minimized, and the position of the important bits such as INTRADC and MVD can be known. Class is separated using the position of these important bits, and variable puncturing tables are designed by the class informations and the code rates of turbo codes are differently designed in according to the class. Channel coding used the turbo codes, and an interleaver to be designed in the turbo codes does not eliminate redundancy bits of the important bits in applying variable code rates of EREC sub-frames unit and is always the same at the transmitter and the receiver although being variable frame size. As a result of simulation, UEP with the code rate similar to EEP is obtained a improved result in the side of bit error probability. And the result of applying it to image knows that the subjective and objective quality have been improved by the protection of important bits.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.45 no.3
• /
• pp.74-79
• /
• 2008

In an H.264/AVC video encoder, the motion estimation at fractional pixel accuracy improves a coding efficiency and image quality. However, it requires additional computation overheads for fractional search and interpolation, and thus, reducing the computation complexity of fractional search becomes more important. This paper proposes fast fractional search algorithms by combining the SASR(Simplified Adaptive Search Range) and the MSDSP(Mixed Small Diamond Search Pattern) with the predicted fractional motion vector. Compared with the full search and the prediction-based directional fractional pixel search, the proposed algorithms can reduce up to 93.2% and 81% of fractional search points, respectively with the maximum PSNR lost less than 0.04dB. Therefore, the proposed fast search algorithms are quite suitable for mobile applications requiring low power and complexity.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.39 no.2
• /
• pp.11-21
• /
• 2002

Although the matching Pursuit is effective for video coding at low bit rate, it has a Problem since it needs much more calculation than the conventional block-based video coding method. The proposed fast matching pursuit method reduces inner product calculation that takes the most part of entire calculation by utilizing the symmetry of the absolute values of the one-dimensional Gator dictionary bases, the modified dictionary which allows faster matching without causing image quality degradation, and a Property of the two-dimensional Gabor dictionary that can be grouped in advance to four classes according to its frequency characteristics. Proposed method needs only about 1/8 of multiplications compared to the well-known separability-based fast method proposed by Neff.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.15 no.3
• /
• pp.221-231
• /
• 1990

In this paper, A new 2-D DCT algorithm is proposed to reduce the computational amount of transform operation using the distribution of the motion compensated error signal and the bit allocation table. In the this algorithm, 2-D Walsh-Hadamard transform is directly computed and then multiplied by a constant matrix. Multiplications are concentrated on the final stage in thie algorithm, thus the computational amount is reduced in proportion to the number of transform coefficients that are excluded from quatization. The computational amount in computing only the DCT coefficients allocated to the bit allocation table is calculated. As the result, the number of multiplications is less thn the algorithm known to have the fewest number of computations when less than 0.6 bits per pixel are allocated to tranform coding for the motion compensated error image in the case of the proposed algorithm. Thus, it shows that the proposed algorithm is valid in reducing the computational loads of transform coding.

• The Transactions of the Korea Information Processing Society
• /
• v.7 no.10
• /
• pp.3290-3299
• /
• 2000

Digital watermarking has similar concepts with channel coding thechnique for transferring data with minimizing error in noise environment, since it should be robust to various kinds of data manipulation for protecting copyrights of multimedia data. This paper proposes a digital watermarking technique which is robust to various kinds of data manipulation. Intellectual property rights information is encoded using a convolutional code, and block-interleaving technique is applied to prevent successive loss of encoded data. Encoded intelloctual property rithts informationis embedded using spread spectrum technique which is robust to cata manipulation. In order to reconstruct intellectual property rights information, watermark signalis detected by covariance between watermarked image and pseudo rando noise sequence which is used to einbed watermark. Embedded intellectual property rights information is obtaned by de-interleaving and cecoding previously detected wtermark signal. Experimental results show that block interleaving watermarking technique can detect embedded intellectial property right informationmore correctly against to attacks like Gaussian noise additon, filtering, and JPEG compression than general spread spectrum technique in the same PSNR.

• Journal of Korea Multimedia Society
• /
• v.9 no.5
• /
• pp.529-541
• /
• 2006

In this paper, we propose a semi-automatic segmentation method which can be used to generate video object plane (VOP) for object based coding scheme and multimedia authoring environment. Semi-automatic segmentation can be considered as a user-assisted segmentation technique. A user can initially mark objects of interest around the object boundaries and then the selected objects are continuously separated from the un selected areas through time evolution in the image sequences. The proposed segmentation method consists of two processing steps: partially manual intra-frame segmentation and fully automatic inter-frame segmentation. The intra-frame segmentation incorporates user-assistance to define the meaningful complete visual object of interest to be segmentation and decides precise object boundary. The inter-frame segmentation involves boundary and region tracking to obtain temporal coherence of moving object based on the object boundary information of previous frame. The proposed method shows stable and efficient results that could be suitable for many digital video applications such as multimedia contents authoring, content based coding and indexing. Based on this result, we have developed objects based video editing system with several convenient editing functions.

• The Journal of the Korea Contents Association
• /
• v.18 no.12
• /
• pp.35-45
• /
• 2018

Motion Estimation(ME) has been developed to reduce the redundant data in digital video signal. ME is an important part of video encoding system, However, it requires huge computational complexity of the encoder part, and fast motion search methods have been proposed to reduce huge complexity. Multi- view video is obtained by capturing on a three-dimensional scene with many cameras at different positions and its complexity increases in proportion to the number of cameras. In this paper, we proposed an efficient motion method which chooses a search pattern adaptively by using the temporal-spatial correlation of the block and the characteristics of the block. Experiment results show that the computational complexity reduction of the proposed method over TZ search method and FS method can be up to 70~75% and 99% respectively while keeping similar image quality and bit rates.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.17 no.2
• /
• pp.435-449
• /
• 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 Society of Broadcast Engineers Conference
• /
• 2020.11a
• /
• pp.145-147
• /
• 2020

As deep learning technology advances, there have been many attempts to improve video codecs such as High-Efficiency-Video-Coding (HEVC) using deep learning technology. One of the most researched approaches is improving filters inside codecs through image restoration researches. In this paper, we propose a method 01 replacing the sample adaptive offset (SAO) filtering with a deep neural network. The proposed method uses the deep neural network to find the optimal offset value. The proposed network consists of two subnetworks to find the offset value and its type of the signal, which can restore nonlinear and complex type of error. Experimental results show that the performance is better than the conventional HEVC in low delay P and random access mode.

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