582 research outputs found
Real-time complexity constrained encoding
Complex software appliances can be deployed on hardware with limited available computational resources. This computational boundary puts an additional constraint on software applications. This can be an issue for real-time applications with a fixed time constraint such as low delay video encoding. In the context of High Efficiency Video Coding (HEVC), a limited number of publications have focused on controlling the complexity of an HEVC video encoder. In this paper, a technique is proposed to control complexity by deciding between 2Nx2N merge mode and full encoding, at different Coding Unit (CU) depths. The technique is demonstrated in two encoders. The results demonstrate fast convergence to a given complexity threshold, and a limited loss in rate-distortion performance (on average 2.84% Bjontegaard delta rate for 40% complexity reduction)
Complexity Analysis Of Next-Generation VVC Encoding and Decoding
While the next generation video compression standard, Versatile Video Coding
(VVC), provides a superior compression efficiency, its computational complexity
dramatically increases. This paper thoroughly analyzes this complexity for both
encoder and decoder of VVC Test Model 6, by quantifying the complexity
break-down for each coding tool and measuring the complexity and memory
requirements for VVC encoding/decoding. These extensive analyses are performed
for six video sequences of 720p, 1080p, and 2160p, under Low-Delay (LD),
Random-Access (RA), and All-Intra (AI) conditions (a total of 320
encoding/decoding). Results indicate that the VVC encoder and decoder are 5x
and 1.5x more complex compared to HEVC in LD, and 31x and 1.8x in AI,
respectively. Detailed analysis of coding tools reveals that in LD on average,
motion estimation tools with 53%, transformation and quantization with 22%, and
entropy coding with 7% dominate the encoding complexity. In decoding, loop
filters with 30%, motion compensation with 20%, and entropy decoding with 16%,
are the most complex modules. Moreover, the required memory bandwidth for VVC
encoding/decoding are measured through memory profiling, which are 30x and 3x
of HEVC. The reported results and insights are a guide for future research and
implementations of energy-efficient VVC encoder/decoder.Comment: IEEE ICIP 202
A Deeply Pipelined CABAC Decoder for HEVC Supporting Level 6.2 High-tier Applications
High Efficiency Video Coding (HEVC) is the latest video coding standard that specifies video resolutions up to 8K Ultra-HD (UHD) at 120 fps to support the next decade of video applications. This results in high-throughput requirements for the context adaptive binary arithmetic coding (CABAC) entropy decoder, which was already a well-known bottleneck in H.264/AVC. To address the throughput challenges, several modifications were made to CABAC during the standardization of HEVC. This work leverages these improvements in the design of a high-throughput HEVC CABAC decoder. It also supports the high-level parallel processing tools introduced by HEVC, including tile and wavefront parallel processing. The proposed design uses a deeply pipelined architecture to achieve a high clock rate. Additional techniques such as the state prefetch logic, latched-based context memory, and separate finite state machines are applied to minimize stall cycles, while multibypass- bin decoding is used to further increase the throughput. The design is implemented in an IBM 45nm SOI process. After place-and-route, its operating frequency reaches 1.6 GHz. The corresponding throughputs achieve up to 1696 and 2314 Mbin/s under common and theoretical worst-case test conditions, respectively. The results show that the design is sufficient to decode in real-time high-tier video bitstreams at level 6.2 (8K UHD at 120 fps), or main-tier bitstreams at level 5.1 (4K UHD at 60 fps) for applications requiring sub-frame latency, such as video conferencing
Random Linear Network Coding for 5G Mobile Video Delivery
An exponential increase in mobile video delivery will continue with the
demand for higher resolution, multi-view and large-scale multicast video
services. Novel fifth generation (5G) 3GPP New Radio (NR) standard will bring a
number of new opportunities for optimizing video delivery across both 5G core
and radio access networks. One of the promising approaches for video quality
adaptation, throughput enhancement and erasure protection is the use of
packet-level random linear network coding (RLNC). In this review paper, we
discuss the integration of RLNC into the 5G NR standard, building upon the
ideas and opportunities identified in 4G LTE. We explicitly identify and
discuss in detail novel 5G NR features that provide support for RLNC-based
video delivery in 5G, thus pointing out to the promising avenues for future
research.Comment: Invited paper for Special Issue "Network and Rateless Coding for
Video Streaming" - MDPI Informatio
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