To provide excellent visual experience for customers, virtual reality (VR) sources require higher resolutions and better visual quality than traditional picture sequences. The content of a VR video can be mapped into a sphere by playing devices to present a $360^{\circ }$ scene, which is usually called VR360 in industrial community. The most popular formats for VR360 sources are the equirectangular projection (ERP) and the cubemap projection (CMP). Both ERP and CMP pictures can be effectively projected to a virtual three-dimensional spherical surface for rendering. It brings a new challenge to the compression of VR video sources, which is how to reallocate proper bit-rate to match mainstream projection formats. The most intuitive way to deal with this challenge is to empirically assign a fixed quantization parameter (QP) to each coding unit according to its position, which evidently lacks precision, rationality, and thus, degrades coding performance. This research proposes a new entropy equilibrium optimization (EEO) methodology to enhance the coding performance of VR360 videos. Specifically, we develop a spherical bit-rate equalization strategy to obtain a block-level Lagrangian multiplier ($lambda$, $\lambda$) for the rate-distortion optimization process in video coding. The appropriate QP value for each block is then dynamically determined in accordance with its $\lambda$. Based on our EEO methodology, we develop two algorithms, EEOA-ERP and EEOA-CMP, to enhance compression efficiency for the ERP and CMP pictures, respectively. Experimental results demonstrate that both algorithms achieve significant BD-Rate savings and outperform the HM16.17 platform for all-intra (AI), low-delay (LD) and random-access (RA) configurations, respectively. Concretely, compared with the state-of-the-art algorithm WSU-ERP, the proposed EEOA-ERP achieves BD-Rate saving of 0.37% in LD configuration. Furthermore, the proposed EEOA-CMP gains 2.6% on objective quality in RA configuration when compared with the HM16.17 VR CMP under the common test condition.

中文翻译：

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虚拟现实 360 度源的视频编码优化

为了为客户提供出色的视觉体验，虚拟现实 (VR) 源需要比传统图片序列更高的分辨率和更好的视觉质量。VR视频的内容可以通过播放设备映射到一个球体中，呈现一个$360^{\circ }$场景，在工业界通常称为VR360。VR360 源最流行的格式是等距柱状投影 (ERP) 和立方体贴图投影 (CMP)。ERP 和 CMP 图片都可以有效地投影到虚拟的三维球面进行渲染。这给VR视频源的压缩带来了新的挑战，即如何重新分配合适的码率以匹配主流投影格式。应对这一挑战最直观的方法是根据每个编码单元的位置经验性地为每个编码单元分配一个固定的量化参数（QP），这显然缺乏精确性、合理性，从而降低了编码性能。本研究提出了一种新的熵平衡优化 (EEO) 方法来提高 VR360 视频的编码性能。具体来说，$拉姆达$, $\lambda$) 用于视频编码中的率失真优化过程。然后根据其动态确定每个块的适当 QP 值$\lambda$. 基于我们的 EEO 方法，我们开发了两种算法，EEOA-ERP 和 EEOA-CMP，以分别提高 ERP 和 CMP 图片的压缩效率。实验结果表明，两种算法都实现了显着的 BD-Rate 节省，并且分别在全帧内 (AI)、低延迟 (LD) 和随机访问 (RA) 配置方面优于 HM16.17 平台。具体而言，与最先进的算法 WSU-ERP 相比，所提出的 EEOA-ERP 在 LD 配置中实现了 0.37% 的 BD-Rate 节省。此外，与普通测试条件下的 HM16.17 VR CMP 相比，所提出的 EEOA-CMP 在 RA 配置中的客观质量提高了 2.6%。