低空通信环境下基于双层博弈的LCU级视频比特分配算法

张雅霏; 刘露露; 于金池; 朱迪锋; 龚轩; 高毅

doi:10.13700/j.bh.1001-5965.2025.0357

低空通信环境下基于双层博弈的LCU级视频比特分配算法

doi: 10.13700/j.bh.1001-5965.2025.0357

张雅霏^{1, 2},
刘露露¹,
于金池^{1, 2},
朱迪锋^{1, 3, ,},
龚轩¹,
高毅¹

1.
北京航空航天大学杭州创新研究院，杭州 310051
2.
北京航空航天大学软件学院，北京 100191
3.
浙江越秀外国语学院，绍兴 312030

基金项目:

浙江省“尖兵”“领雁”研发攻关计划(2024C01079)

详细信息

通讯作者:
E-mail：zhudf@buaa.edu.cn

中图分类号: V221⁺.3；TB553
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- 文章访问数: 18
- HTML全文浏览量: 1
- PDF下载量: 1
- 被引次数: 0
出版历程
- 收稿日期: 2025-06-09
- 录用日期: 2025-08-15
- 网络出版日期: 2025-09-03
- 整期出版日期: 2026-09-01

LCU-level video bit allocation algorithm based on two-layer game in low-altitude communication environment

ZHANG Yafei^{1, 2},
LIU Lulu¹,
YU Jinchi^{1, 2},
ZHU Difeng^{1, 3
, ,},
GONG Xuan¹,
GAO Yi¹

1.
Hangzhou Innovation Institute of Beihang University，Hangzhou 310051，China
2.
School of Software，Beihang University，Beijing 100191，China
3.
Zhejiang Yuexiu University，Shaoxing 312030，China

Funds:

Zhejiang Provincial “Pioneer” and “Leading Goose” R&D Program (2024C01079)

More Information

Corresponding author: E-mail：zhudf@buaa.edu.cn

摘要

摘要:
针对低空通信场景下视频编码效率低与码率利用率不足的问题，提出一种基于双层混合博弈模型的最大编码单元(LCU)级比特分配(BA)优化(HGLA)算法。该算法以LCU为基本单元，依据纹理复杂度、运动强度与边缘信息进行区域划分，并构建高、低复杂度区域的差异化BA机制，其中，高复杂度区域通过非合作博弈与合作博弈相结合实现比特协调分配，低复杂度区域引入空间加权机制以提高码率利用率，并采用全局量化参数(QP)平滑策略增强视觉连续性。在4种低码率场景下进行实验验证，所提算法在峰值信噪比(PSNR)、结构相似性指数(SSIM)和主观质量方面均取得显著提升，特别是在目标码率为16 Kbit/s时，相比高效视频编码(HEVC)模型采用的码率控制(RC)算法HM-RC、基于帧级多层感知机(MLP)的BA 算法、基于简化立方率失真模型的帧内RC算法、基于通用视频编码(VVC)的变分辨率RC算法4种典型算法，PSNR、SSIM和主观意见得分(MOS)分别平均提升了3.34%、2.16%和9.8%，表明其在码率利用效率和图像质量保持方面具有良好的实用性与适应性。
- 码率控制 /
- 低码率 /
- 博弈论 /
- 比特分配 /
- 低空视频可靠传输
Abstract:
This paper addresses the issues of low video coding efficiency and insufficient bit rate utilization in low-altitude communication scenarios by proposing an largest coding unit (LCU)-level bit allocation (BA) optimization based on two-layer hybrid game model (HGLA) algorithm. Using the LCU as the basic unit, the algorithm performs region partitioning according to texture complexity, motion intensity, and edge information, and establishes a differentiated BA mechanism for high- and low-complexity regions. In particular, a combination of cooperative and non-cooperative game models is used for high-complexity regions to achieve coordinated BA; for low-complexity regions, a global quantization parameter (QP) smoothing strategy and a spatial weighting mechanism are introduced to improve bit rate utilization efficiency and visual continuity. Finally, experimental validation under four low-bit rate scenarios demonstrates that the proposed method achieves significant improvements in peak signal-to-noise ratio (PSNR), structural similarity index measure (SSIM), and subjective quality. Specifically, at the target bit rate of 16 Kbit/s, compared with four baseline methods including the high efficiency video coding (HEVC) rate control (RC) algorithm HM-RC and the frame-level multilayer perceptron (MLP)-based BA algorithm, the intra-frame rate control algorithm based on a simplified cubic rate-distortion model, and the variable-resolution rate control algorithm based on versatile video coding (VVC), the proposed method achieves average performance gains of 3.34%, 2.16%, and 9.8% in PSNR, SSIM, and mean opinion score (MOS), respectively, demonstrating its excellent practicality and adaptability in improving bit rate utilization efficiency and preserving image quality.
- rate control /
- low bit rate /
- game theory /
- bit allocation /
- reliable transmission of low-altitude video

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图 1 低空通信环境下低码率视频传输

Figure 1. Low bit rate video transmission in low-altitude communication environment

下载: 全尺寸图片幻灯片

图 2 HGLA算法

Figure 2. HGLA algorithm

下载: 全尺寸图片幻灯片

表 1 HEVC 测试序列

Table 1. HEVC test sequence

类别	序列名称	帧数	帧率/(帧·s⁻¹)
A	Traffic	150	30
A	PeopleOnStreet	150	30
A	Nebuta	300	60
A	SteamLocomotive	300	60
B	Kimono	240	24
B	ParkScene	240	24
B	Cactus	500	50
B	BasketballDrive	500	50
C	RaceHorses	300	30
C	BQMall	600	60
C	PartyScene	500	50
C	BasketballDrill	500	50
D	RaceHorses	300	30
D	BQSquare	600	60
D	BlowingBubbles	500	50
D	BasketballPass	500	50

下载: 导出CSV

表 2 目标码率为16 Kbit/s场景下实验对比

Table 2. Experimental comparison under the target bit rate of 16 Kbit/s

算法	PSNR/dB	SSIM	MOS
文献[22]	32.50	0.869	3.14
文献[23]	33.06	0.887	3.25
文献[24]	33.53	0.891	3.45
HM-RC	32.01	0.862	3.08
本文	33.86	0.896	3.54

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表 3 目标码率为128 Kbit/s场景下实验对比

Table 3. Experimental comparison under the target bit rate of 128 Kbit/s

算法	PSNR/dB	SSIM	MOS
文献[22]	36.57	0.914	3.40
文献[23]	37.18	0.928	3.73
文献[24]	37.74	0.931	4.01
HM-RC	36.01	0.906	3.35
本文	37.89	0.934	4.05

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表 4 目标码率为256 Kbit/s场景下实验对比

Table 4. Experimental comparison under the target bit rate of 256 Kbit/s

算法	PSNR/dB	SSIM	MOS
文献[22]	38.72	0.921	3.84
文献[23]	39.18	0.936	4.06
文献[24]	39.63	0.940	4.12
HM-RC	38.27	0.918	3.68
本文	39.71	0.945	4.26

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表 5 目标码率为512 Kbit/s场景下实验对比

Table 5. Experimental comparison under the target bit rate of 512 Kbit/s

算法	PSNR/dB	SSIM	MOS
文献[22]	40.54	0.930	4.03
文献[23]	41.13	0.948	4.25
文献[24]	41.58	0.952	4.39
HM-RC	40.09	0.926	3.96
本文	41.76	0.957	4.41

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表 6 本文提出的各项因子对HGLA算法的影响

Table 6. The influence of various factors proposed in this paper on the HGLA algorithm

实验配置	PSNR/dB	SSIM	MOS
HGLA	41.76	0.957	4.41
无区域划分模型	40.05	0.944	3.92
仅非合作博弈	40.49	0.948	4.01
无空间权重	41.31	0.949	4.07
无QP平滑处理	41.54	0.951	4.10

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