Younghyeon Park

Early Skip Mode Decision for HEVC Encoder With Emphasis on Coding Quality

Although High Efficiency Video Coding (HEVC) is suitable for high definition (HD) and ultra-HD video services due to its high compression efficiency and excellent coded picture quality, its high encoding complexity is an obstacle for wide-spread practical applications. Although many fast coding schemes can alleviate the complexity problem, their coding quality suffers much. In this paper, an early skip mode decision is proposed to reduce the encoding complexity of HEVC while not sacrificing its coding quality much. The proposed method determines the skip mode by utilizing its distortion characteristics just after calculating rate-distortion cost of 2N × 2N merge mode, and those prediction units decided as the skip mode do not undergo remaining mode decision processes. The threshold for the early decision is estimated directly from the video data themselves. Experimental results show that the proposed method achieves encoding complexity reduction of 30.1% in random access main condition and 26.4% in low-delay main condition on average with virtually no coding loss compared to the HEVC full rate-distortion optimized decision.

Fast Quantization Method With Simplified Rate–Distortion Optimized Quantization for an HEVC Encoder

While the rate-distortion optimized quantization (RDOQ) technique provides nontrivial coding gain in High Efficiency Video Coding (HEVC), it also involves considerable computations, whereby the complexity of quantization is significantly increased. In this paper, two schemes (the RDOQ bypass decision and the simplified level adjustment) are investigated to reduce the complexity of the quantization process in HEVC with RDOQ. The RDOQ bypass decision method initially selects the transform blocks for which the RDOQ is expected to give less/or no coding gain and enables the conventional uniform scalar quantization to be applied to these transform blocks instead of the RDOQ. The simplified level adjustment method only estimates the difference in rate-distortion costs among the candidate quantization levels to enable the encoder to select an optimal quantization level at a much reduced computational cost. Furthermore, the proposed simplified level adjustment scheme is designed so that it can be implemented in lookup tables. Experimental results show that the proposed fast method achieves 14.3% quantization complexity reduction in all intra main conditions, 15.2% in the random access main condition, and 14.9% in the low delay main condition on average with virtually no coding loss compared with the conventional quantization process with the RDOQ.

Measurement Coding for Compressive Sensing of Color Images

From the perspective of reducing the sampling cost of color images at high resolution, block-based compressive sensing (CS) has attracted considerable attention as a promising alternative to conventional Nyquist/Shannon sampling. On the other hand, for storing/transmitting applications, CS requires a very efficient way of representing the measurement data in terms of data volume. This paper addresses this problem by developing a measurement-coding method with the proposed customized Huffman coding. In addition, by noting the difference in visual importance between the luma and chroma channels, this paper proposes measurement coding in YCbCr space rather than in conventional RGB color space for better rate allocation. Furthermore, as the proper use of the image property in pursuing smoothness improves the CS recovery, this paper proposes the integration of a low pass filter to the CS recovery of color images, which is the block-based l 20 -norm minimization. The proposed coding scheme shows considerable gain compared to conventional measurement coding.

Optimal complexity scalable H.264/AVC video decoding scheme for portable multimedia devices

Abstract. Limited computing resources in portable multimedia devices are an obstacle in real-time video decoding of high resolution and/or high quality video contents. Ordinary H.264/AVC video decoders cannot decode video contents that exceed the limits set by their processing resources. However, in many real applications especially on portable devices, a simplified decoding with some acceptable degradation may be desirable instead of just refusing to decode such contents. For this purpose, a complexity-scalable H.264/AVC video decoding scheme is investigated in this paper. First, several simplified methods of decoding tools that have different characteristics are investigated to reduce decoding complexity and consequential degradation of reconstructed video. Then a complexity scalable H.264/AVC decoding scheme is designed by selectively combining effective simplified methods to achieve the minimum degradation. Experimental results with the H.264/AVC main profile bitstream show that its decoding complexity can be scalably controlled, and reduced by up to 44% without subjective quality loss.

A Skip-mode Coding for Distributed Compressive Video Sensing

분산 압축 비디오 센싱 (DCVS) 기술은 압축센싱 및 분산 비디오 부호화 기술의 결합을 통해 저 비용의 샘플링을 실현하는 새로운 패러다임이다. 본 논문에서는 프레임 간 높은 시간 상관성을 활용한 DCVS에서의 스킵모드 부호화 방법을 제안한다. 제안하는 방법은 일정조건을 만족하는 비 키-프레임에 대한 측정값을 복호화기에 전송하지 않아도 시간적 보간법을 통해 해당 비 키-프레임의 복원이 가능하도록 하여 율-왜곡 측면에서 좋은 압축 성능을 보장한다. 이와 더불어, 더 나은 시간적 보간을 위하여 계층적 구조를 사용하는 방법을 제안한다. 실험 결과, 제안하는 스킵모드 부호화 방법은 약간의 PSNR 감소에 비해 매우 높은 측정율 절약이 되는 것을 확인하였다. 또한, 제안하는 방법을 높은 시간 연관성을 갖는 비디오 영상에 적용할 경우, 복호화기의 연산 복잡도가 평균 43.75% 감소하는 것을 확인하였다.

Visible and near-infrared image separation from CMYG color filter array based sensor

Simultaneous acquisition of visible and near-infrared images is useful for various image enhancement techniques. In this paper, we study a method for visible and near-infrared image separation from an image captured by a single sensor with cyan, magenta, yellow, and green color filter array. The proposed separation method is mathematically simple, and its hardware can be also implemented by only slight modification of conventional camera. Experimental results observed that a single CMYG-NIR mixed image can be separated into the RGB and MR images.

Rate Allocation for Block-based Compressive Sensing

희소성이 높은 신호를 압축센싱을 할 경우 기존의 Nyquist/Shannon 이론을 바탕으로 하는 샘플링 방법 보다 낮은 측정율 만으로도 신호의 복원이 가능하기 때문에 이를 활용한 많은 응용 연구가 이루어지고 있다. 영상신호의 경우 특히 블록기반 압축센싱 기법이 주로 고려되고 있는데, 대부분의 경우 측정 영역에서의 공간적 유사도가 동일하다는 가정 하에, 각 블록에 동일한 측정율을 할당하여 왔다. 이를 개선하기 위해, 본 논문에서는 프레임 내의 각 블록에 대하여 경계선 정보를 구하고, 각각의 특성에 따르는 적응적 샘플링율 기법을 제안한다. 제안하는 방법은 측정영역에서의 블록 간 유사도를 구해서 경계선 정보를 많이 포함하는 블록일수록 많은 측정율을 할당한다. 실험 결과, 자연영상에 대해 제안하는 적응적 율 할당 기법은 고정 측정율을 사용한 기존 방법에 비해 객관적 (최대 3.29 dB 향상) 및 주관적 화질이 뛰어나다는 것을 보여준다.