Mixed-resolution HEVC based multiview video codec for low bitrate transmission

Mallik, Bruhanth; Sheikh-Akbari, Akbar; Kor, Ah-Lian

doi:10.1007/s11042-018-6272-2

Cited by 7 publications

(4 citation statements)

References 22 publications

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“…There are three other methods implemented for performance comparison. The hybrid low-resolution multi-view video coding method, MRMV [25], uses the low-resolution image as the auxiliary information. The images of even views are downsampled and further reconstructed during the encoding and decoding processes.…”

Section: Methodsmentioning

confidence: 99%

Multi-View Video Coding with GAN Latent Learning

Lan¹,

Luo²,

Yan³

et al. 2022

Preprint

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The introduction of multiple viewpoints inevitably increases the bitrates to store and transmit video scenes. To reduce the compressed bitrates, researchers have developed to skip intermediate viewpoints during compression and delivery, and finally reconstruct them with Side Information (SI). Generally, the depth maps can be utilized to construct SI; however, it shows inferior performance with inaccurate reconstruction or high bitrates. In this paper, we propose a multi-view video coding based on SI of Generative Adversarial Network (GAN). At the encoder, we construct a spatio-temporal Epipolar Plane Image (EPI) and further utilize convolutional network to extract the latent code of GAN as SI; while at the decoder side, we combine the SI and adjacent viewpoints to reconstruct intermediate views by the generator of GAN. In particular, we set a joint encoder constraint of reconstruction cost and SI entropy, in order to achieve an optimal tradeoff between reconstruction quality and bitrate overhead. Experiments show a significantly improved Rate-Distortion (RD) performance compared with the state-of-the-art methods.

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Section: Methodsmentioning

confidence: 99%

Multi-View Video Coding with GAN Latent Learning

Lan¹,

Luo²,

Yan³

et al. 2022

Preprint

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show abstract

“…For large amounts of video data and high visual quality requirements, video codec technology has been rapidly developed and has become much more mature. In [12], a high-efficiency video codec-based spatial resolution scaling type for mixed resolution coding for frame interleaved multiview videos was proposed. In [13], the authors proposed a novel video transmission strategy that effectively transfers the computational complexity of video coding from the terminal to the cloud environment.…”

Section: Related Workmentioning

confidence: 99%

A Novel Model for Large-Scale Online College Learning in Postpandemic Era: AI-Driven Approach

Wang

2021

Mobile Information Systems

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COVID-19 is a pandemic with a wide reach and explosive magnitude, and the world has been bracing itself for impact. Many have lost their jobs and savings, and many are homeless. For better or worse, COVID-19 has permanently changed our lives. For college students, the pandemic means giving up most of the on-campus experience in the postpandemic era and performing online learning instead. Virtual lessons may become a permanent part of college education. Large-scale online learning typically utilizes interactive live video streaming. In this study, we analyzed a codec and video streaming transmission protocol using artificial intelligence. First, we studied an intraframe prediction optimization algorithm for the H.266 codec based on long short-term memory networks. In terms of video streaming transmission protocols, real-time communication optimization based on Quick UDP Internet connections and Luby Transform codes is proposed to improve the quality of interactive live video streaming. Experimental results demonstrate that the proposed strategy outperforms three benchmarks in terms of video streaming quality, video streaming latency, and average throughput.

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“…In the HEVC method, blocking artifacts are observed at low bitrates due to its large block size, different partition blocks, different chroma, and luma components [22][23][24][25][26][27][28][29][30][31]. De-blocking Filter (DBF) used for the chroma component is simple.…”

Section: Motivation and Contributionmentioning

confidence: 99%

Fuzzy Based Adaptive Deblocking Filters at Low-Bitrate HEVC Videos for Communication Networks

Gandam¹,

Sidhu²

2021

Computers, Materials &Amp; Continua

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In-loop filtering significantly helps detect and remove blocking artifacts across block boundaries in low bitrate coded High Efficiency Video Coding (HEVC) frames and improves its subjective visual quality in multimedia services over communication networks. However, on faster processing of the complex videos at a low bitrate, some visible artifacts considerably degrade the picture quality. In this paper, we proposed a four-step fuzzy based adaptive deblocking filter selection technique. The proposed method removes the quantization noise, blocking artifacts and corner outliers efficiently for HEVC coded videos even at low bit-rate. We have considered Y (luma), U (chromablue), and V (chroma-red) components parallelly. Finally, we have developed a fuzzy system to detect blocking artifacts and use adaptive filters as per requirement in all four quadrants, namely up 45 • , down 45 • , up 135 • , and down 135 • across horizontal and vertical block boundaries. In this context, experimentation is done on a wide variety of videos. An objective and subjective analysis is carried out with MATLAB software and Human Visual System (HVS). The proposed method substantially outperforms existing postprocessing deblocking techniques in terms of YPSNR and BD_rate. In the proposed method, we achieved 0.32-0.97 dB values of YPSNR. Our method achieved a BD_rate of +1.69% for the luma component, −0.18% (U) and −1.99% (V) for chroma components, respectively, with respect to the stateof-the-art methods. The proposed method proves to have low computational complexity and has better parallel processing, hence suitable for a real-time system in the near future.

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Mixed-resolution HEVC based multiview video codec for low bitrate transmission

Cited by 7 publications

References 22 publications

Multi-View Video Coding with GAN Latent Learning

Multi-View Video Coding with GAN Latent Learning

A Novel Model for Large-Scale Online College Learning in Postpandemic Era: AI-Driven Approach

Fuzzy Based Adaptive Deblocking Filters at Low-Bitrate HEVC Videos for Communication Networks

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