• IEIE Transactions on Smart Processing and Computing
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• v.6 no.2
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• pp.93-101
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• 2017

This paper proposes an algorithm for adaptive loop filter (ALF) complexity reduction in the decoding process. In the original ALF algorithm, filtering for I frames is performed in the frame unit, and thus, all of the pixels in a frame are filtered if the current frame is an I frame. The proposed algorithm is designed on top of the local gradient calculation. On both the encoder side and the decoder side, homogeneous areas are checked and skipped in the filtering process, and the filter coefficient calculation is only performed in the inhomogeneous areas. The proposed algorithm is implemented in Joint Exploration Model (JEM) version 3.0 future video coding reference software. The proposed algorithm is applied for frame-level filtering and intra configuration. Compared with the JEM 3.0 anchor, the proposed algorithm has 0.31%, 0.76% and 0.73% bit rate loss for luma (Y) and chroma (U and V), respectively, with about an 8% decrease in decoding time.

• IEIE Transactions on Smart Processing and Computing
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• v.5 no.5
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• pp.366-373
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• 2016

This paper proposes a pre-processing algorithm to improve the coding efficiency of perceptual video coding. First, an input image is decomposed into multiple sub-bands through linear sub-band decomposition. Then, the sub-bands that have low visual sensitivity are suppressed by assigning small gains to them. Experimental results show that if the proposed algorithm is adopted for pre-processing in a High Efficiency Video Coding (HEVC) encoder, it can provide significant bit-saving effects of approximately 12% in low delay mode and 9.4% in random access mode.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.8
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• pp.1444-1456
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• 2011

This paper presents a low-complexity algorithm for an H.264/AVC encoder. The proposed motion estimation scheme determines the best coding mode for a given macroblock (MB) by finding motion-blurred MBs; identifying, before motion estimation, an early selection of MBs; and hence saving processing time for these MBs. It has been observed that human vision is more sensitive to the movement of well-structured objects than to the movement of randomly structured objects. This study analyzed permissible perceptual distortions and assigned a larger inter-mode value to the regions that are perceptually less sensitive to human vision. Simulation results illustrate that the algorithm can reduce the computational complexity of motion estimation by up to 47.16% while maintaining high compression efficiency.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2011.11a
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• pp.267-269
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• 2011

본 논문에서는 기존에 제시된 LB 기법을 이용할 경우 발생하는 증가한 복잡도를 감소 시키는 기법을 다룬다. LB(Large Block)는 HEVC(High Efficiency Video Coding)의 대표적인 부호화 툴로 H.264/SVC(Scalable Video Coding)에 적용한 경우에도 상당한 부호화 효율의 개선을 보인다. 그러나, LB 를 적용하면 매크로블록 레벨에서 추가적인 부호화 과정이 요구되므로, 부호화기의 복잡도가 증가하는 문제점이 발생한다. 따라서, 본 논문에서는 LB 를 적용한 SVC 의 부호화기 복잡도를 감소시키는 기법을 제시하고 모의실험을 통해 제안된 부호화 기법의 RD 성능과 부호화기 복잡도를 확인한다. 실험결과 제안된 기법을 사용한 부호화 기법이 기존의 부호화 방법에 비해, RD 측면에서 평균 1.8%의 미미한 손실이 있으나, 복잡도 측면에서 평균 12%의 이득이 있음을 확인 하였다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2018.06a
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• pp.149-151
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• 2018

H.265/HEVC(High Efficiency Video Coding)에서는 하드웨어 비디오 인코더의 처리율(Throughput)을 높이기 위하여 동일 CU(Coding Unit) 내 PU(Prediction Unit)들이 병렬로 머지 후보 리스트를 생성할 수 있는 병렬 머지 방법이 표준 기술로 사용되고 있다. 하지만 이 방법은 동일 CU 내의 PU 간의 의존성만 제거할 수 있고 코딩 순서상의 이전 CU 와의 의존성은 제거할 수 없다. 결국 이전 CU 의 모드 결정 과정이 완료된 후에 현재 CU 내의 PU 가 머지 후보 리스트를 생성할 수 있기 때문에 높은 처리율 향상을 기대할 수 없다. 또한 CU 내의 대부분의 PU 들이 가장 인접한 MV(Motion Vector)를 머지 후보로 사용하지 못하여 압축 효율에 대한 손실도 크다. 본 논문에서는 이전 CU 와의 의존성을 제거함으로써 높은 처리율을 갖으면서 압축 효율에 대한 손실을 최소화할 수 있는 개선된 병렬 머지 방법을 제안한다. 실험 결과, 제안된 방법은 기존 병렬 머지 방법 대비 동일 화질에서 평균 약 1.8%의 압축률이 향상되는 것으로 나타났다.

• Journal of the Korean Society of Industry Convergence
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• v.25 no.4_2
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• pp.707-714
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• 2022

Versatile Video Coding (VVC) is the most recent video coding standard, which had been developed by Joint Video Expert Team (JVET). It can improve significant coding performance compared to the previous standard, namely High Efficiency Video Coding (HEVC). Although VVC can achieve the powerful coding performance, it requires the tremendous computational complexity of VVC encoder. Especially, affine motion compensation (AMC) was adopted the block-based 4-parameter or 6-parameter affine prediction to overcome the limit of translational motion model while VVC require the cost of higher encoding complexity. In this paper, we proposed the early termination of AMC that determines whether the affine motion estimation for AMC is performed or not. Experimental results showed that the proposed method reduced the encoding complexity of affine motion estimation (AME) up to 16% compared to the VVC Test Model 17 (VTM17).

• JSTS:Journal of Semiconductor Technology and Science
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• v.17 no.3
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• pp.446-457
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• 2017

In order to reduce the size of frame memory or bus bandwidth, frame memory compression (FMC) recompresses reconstructed or reference frames of video codecs. This paper proposes a novel FMC design based on discrete wavelet transform (DWT) - set partitioning in hierarchical trees (SPIHT), which supports fine-scalable throughput and is area-efficient. In the proposed design, multi-cores with small block sizes are used in parallel instead of a single core with a large block size. In addition, an appropriate pipelining schedule is proposed. Compared to the previous design, the proposed design achieves the processing speed which is closer to the target system speed, and therefore it is more efficient in hardware utilization. In addition, a scheme in which two passes of SPIHT are merged into one pass called merged refinement pass (MRP) is proposed. As the number of shifters decreases and the bit-width of remained shifters is reduced, the size of SPIHT hardware significantly decreases. The proposed FMC encoder and decoder designs achieve the throughputs of 4,448 and 4,000 Mpixels/s, respectively, and their gate counts are 76.5K and 107.8K. When the proposed design is applied to high efficiency video codec (HEVC), it achieves 1.96% lower average BDBR and 0.05 dB higher average BDPSNR than the previous FMC design.

• Journal of Broadcast Engineering
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• v.21 no.6
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• pp.929-943
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• 2016

This paper proposes the rate control algorithm based on the S-JND (Saliency-Just Noticeable Difference) model for considering perceptual visual quality. The proposed rate control algorithm employs the S-JND model to simultaneously reflect human visual sensitivity and human visual attention for considering characteristics of human visual system. During allocating bits for CTU (Coding Tree Unit) level in a rate control, the bit allocation model calculates the S-JND threshold of each CTU in a picture. The threshold of each CTU is used for adaptively allocating a proper number of bits; thus, the proposed bit allocation model can improve perceptual visual quality. For performance evaluation of the proposed algorithm, the proposed algorithm was implemented on HM 16.9 and tested for sequences in Class B and Class C under the CTC (Common Test Condition) RA (Random Access), Low-delay B and Low-delay P case. Experimental results show that the proposed method reduces the bit-rate of 2.3%, and improves BD-PSNR of 0.07dB and bit-rate accuracy of 0.06% on average. We achieved MOS improvement of 0.03 with the proposed method, compared with the conventional method based on DSCQS (Double Stimulus Continuous Quality Scale).

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2022.06a
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• pp.1191-1194
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• 2022

인터넷의 발전으로 수많은 이미지와 비디오를 손쉽게 이용할 수 있게 되었다. 이미지와 비디오 데이터의 양이 기하급수적으로 증가함에 따라, JPEG, HEVC, VVC 등 이미지와 비디오를 효율적으로 저장하기 위한 부호화 기술들이 등장했다. 최근에는 인공신경망을 활용한 학습 기반 모델이 발전함에 따라, 이를 활용한 이미지 및 비디오 압축 기술에 관한 연구가 빠르게 진행되고 있다. NNIC (Neural Network based Image Coding)는 이러한 학습 가능한 인공신경망 기반 이미지 부호화 기술을 의미한다. 본 논문에서는 NNIC 모델과 인공신경망 기반의 초해상화(Super Resolution) 모델을 합동훈련하여 기존 NNIC 모델보다 더 높은 성능을 보일 수 있는 방법을 제시한다. 먼저 NNIC 인코더(Encoder)에 이미지를 입력하기 전 다운 스케일링(Down Scaling)으로 쌍삼차보간법을 사용하여 이미지의 화소를 줄인 후 부호화(Encoding)한다. NNIC 디코더(Decoder)를 통해 부호화된 이미지를 복호화(Decoding)하고 업 스케일링으로 초해상화를 통해 복호화된 이미지를 원본 이미지로 복원한다. 이때 NNIC 모델과 초해상화 모델을 합동훈련한다. 결과적으로 낮은 비트량에서 더 높은 성능을 볼 수 있는 가능성을 보았다. 또한 합동훈련을 함으로써 전체 성능의 향상을 보아 학습 시간을 늘리고, 압축 잡음을 위한 초해상화 모델을 사용한다면 기존의 NNIC 보다 나은 성능을 보일 수 있는 가능성을 시사한다.

• Journal of Broadcast Engineering
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• v.25 no.3
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• pp.346-352
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• 2020

Versatile Video Coding (VVC), a next-generation video coding standard that is in the final stage of standardization, has adopted various techniques to achieve more than twice the compression performance of HEVC (High-Efficiency Video Coding). VVC adopted Bi-prediction with CU-level Weight (BCW), which generates the final prediction signal with the weighted combination of bi-predictions with various weights, to enhance the performance of the bi-predictive inter prediction. The syntax element of the BCW index is adaptively coded according to the value of NoBackwardPredFlag which indicates if there is no future picture in the display order among the reference pictures. Such syntax structure for signaling the BCW index could violate the flexibility of video codec and cause the dependency issue at the stage of bitstream parsing. To address these issues, this paper proposes an efficient BCW weight signaling method which enables all weights and parsing without any condition check. The performance of the proposed method was evaluated with various weight searching methods in the encoder. The experimental results show that the proposed method gives negligible BD-rate losses and minor gains for 3 weights searching and 5 weights searching, respectively, while resolving the issues.