• Journal of Broadcast Engineering
• /
• v.22 no.2
• /
• pp.193-206
• /
• 2017

In this paper, we propose a rate control method based on the $R-{\lambda}$ model that supports a parallel encoding structure in GOP levels or IDR period levels for 4K UHD input video in real-time. For this, a slice-level bit allocation method is proposed for parallel encoding instead of sequential encoding. When a rate control algorithm is applied in the GOP level or IDR period level parallelism, the information of how many bits are consumed cannot be shared among the frames belonging to a same frame level except the lowest frame level of the hierarchical B structure. Therefore, it is impossible to manage the bit budget with the existing bit allocation method. In order to solve this problem, we improve the bit allocation procedure of the conventional ones that allocate target bits sequentially according to the encoding order. That is, the proposed bit allocation strategy is to assign the target bits in GOPs first, then to distribute the assigned target bits from the lowest depth level to the highest depth level of the HEVC hierarchical B structure within each GOP. In addition, we proposed a processing method that is used to improve subjective image qualities by allocating the bits according to the coding complexities of the frames. Experimental results show that the proposed bit allocation method works well for frame-level parallel HEVC software encoders and it is confirmed that the performance of our rate controller can be improved with a more elaborate bit allocation strategy by using the preprocessing results.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.38 no.2
• /
• pp.129-137
• /
• 2001

Matching pursuit algorithm was successfully demonstrated useful in low bit-rate video coding, However, one of the practical concerns related to applying the matching pursuit algorithm to application is its massive computation required for finding bases whose weighted sum best approximates the given input image. The main contribution of this paper is that we provide a new method that can drastically reduce the computational load without any degradation of image quality. Its main idea is based on reducing the number of inner product calculation required for finding best bases because the complexity of matching pursuit algorithm is due to the exhaustive local inner product calculation. As the first step, we compute a matrix which is the 1-D inner product of the given motion-compensated error input image with the 1-D vertical Gabor functions using the separable property of Gabor bases. In the second step, we calculate length of each vector in the matrix that corresponds to 1-D horizontal Gabor function, and compare the length with the current maximum absolute inner product value so far. According to the result of this comparison, one can decide whether or not to calculate the inner product. Since most of them do not need to calculate the inner product value, one can significantly reduce the computational load. Experimental results show that proposed method reduces about 70% of inner product calculation compared to the Neff's fast algorithm without any degradation of image quality.

• Journal of KIISE:Software and Applications
• /
• v.29 no.1_2
• /
• pp.98-113
• /
• 2002

In this paper, we present advanced algorithms to reduce the computations of block matching algorithms for motion estimation in video coding. Advanced multi-level successive elimination algorithms(AMSEA) are based on the Multi-level successive elimination algorithm(MSEA)[1]. The first algorithm is that when we calculate the sum of absolute difference (SAD) between the sum norms of sub-blocks in MSEA, we use the partial distortion elimination technique. By using the first algorithm, we can reduce the computations of MSEA further. In the second algorithm, we calculate SAD adaptively from large value to small value according to the absolute difference values between pixels of blocks. By using the second algorithm, the partial distortion elimination in SAD calculation can occur early. So, the computations of MSEA can be reduced. In the third algorithm, we can estimate the elimination level of MSEA. Accordingly, the computations of the MSEA related to the level lower than the estimated level can be reduced. The fourth algorithm is a very fast block matching algorithm with nearly 100% motion estimation accuracy. Experimental results show that AMSEA are very efficient algorithms for the estimation of motion vectors.

• Journal of Broadcast Engineering
• /
• v.17 no.4
• /
• pp.640-658
• /
• 2012

One of the existing terrestrial multi-channel DTV service frameworks, called KoreaView, provides four programs, composed of MPEG-2 based one HD video and H.264/AVC based three SD videos within one single 6MHz frequency bandwidth. However the additional 3 SD videos can not provide enough quality due to its reduced spatial resolution and low target bitrates. In this paper, we propose a framework, which is called a terrestrial multi-channel high quality hybrid DTV service, to overcome such a weakness of KoreaView services. In the proposed framework, the three additional SD videos are encoded based on an H.264/SVC Spatial Base layer, which is compliant with H.264/AVC, and are delivered via broadcasting networks. On the other hand, and the corresponding three additional HD videos are encoded based on an H.264/SVC Spatial Enhancement layer, which are transmitted over broadband networks such as Internet, thus allowing the three additional videos for users with better quality of experience. In order to verify the effectiveness of the proposed framework, various experimental results are provided for real video contents being used for DTV services. First, the experimental results show that, when the SD sequences are encoded by the H.264/SVC Spatial Base layer at a target bitrate of 1.5Mbps, the resulting PSNR values are ranged from 34.5dB to 42.9dB, which is a sufficient level of service quality. Also it is noted that 690kbps-8,200kbps are needed for the HD test sequences when they are encoded in the H.264/SVC Spatial Enhancement layer at similar PSNR values for the same HD sequences encoded by MPEG-2 at a target bitrate of 12 Mbps.