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IMAGE SEGMENTATION APPROACH FOR REALIZING ZOOMABLE STREAMING HEVC VIDEO

机译:实现缩放流HEVC视频的图像分割方法

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The next generation compression technology High Efficiency Video Coding (HEVC) can provide a substantially higher compression capability than the existing H.264/AVC standard. It has received increased attention and is lauded as the enabler for a host of new services and capabilities [4]. A better user experience for browsing videos on the limited and heterogeneous screen sizes requires streaming of an arbitrary region of interest (ROI) from a high resolution video. It is essential to support cropping and zooming within a video stream which allows the users to view a cropped ROI at a high resolution, in effect, magnifying the ROI. This paper thesis explores two methods for ROI-based streaming, referring to them as tiled encoding which partitions video frames into grid of tiles and encodes each tile as an independently decodable stream and partial decoding where only the ROI and dependence area are decoded. Apart from these, slice structure dependency on tiled encoding was performed for further bandwidth efficiency. These two methods were evaluated in terms of bandwidth efficiency, storage requirements, and computational costs under different video encoding parameters. HM15.0 version reference software for HEVC was used [8]. Partial decoding results show that the decoding calculation cost was reduced by 40-55% for 32 buffered luma pixels around ROI. Tiled encoding results show optimal decoding calculation cost and bandwidth efficiency for a tile size of 16×16 pixels. Simulation results show that larger tiles significantly improve compression efficiency in tiled encoding, but it would lead to higher bandwidth while a larger slice size increases the bandwidth efficiency (reduces transmission overhead) but would result in lower compression. The results show that 1460 bytes slice structure improved bandwidth efficiency than 64 bytes slice structure.
机译:下一代压缩技术高效视频编码(HEVC)可以提供比现有的H.264 / AVC标准更高的压缩能力。它受到了增加的关注,并作为一系列新服务和能力的推动者参与了[4]。在有限和异构屏幕大小上浏览视频的更好的用户体验需要从高分辨率视频流式兴趣(ROI)的流式传输。必须支持在视频流中裁剪和缩放,这允许用户以高分辨率查看裁剪ROI,实际上放大ROI。本文探讨了基于ROI的流传输的两种方法,参考其作为瓷砖编码,该铺侧编码将视频帧分区为图块的网格并将每个瓦片编码为独立解码的流,并且仅解码ROI和依赖区域的部分解码,其中仅解码ROI和依赖区域。除此之外,对瓷砖编码的切片结构依赖性是为了进一步的带宽效率而进行。在不同视频编码参数下的带宽效率,存储要求和计算成本方面评估这两种方法。 HM15.0版本的HEVC版本参考软件[8]。部分解码结果表明,ROI周围的32个缓冲亮度像素的解码计算成本降低了40-55%。瓷砖编码结果显示了16×16像素的瓷砖大小的最佳解码计算成本和带宽效率。仿真结果表明,较大的瓷砖在瓷砖编码中显着提高压缩效率,但它会导致更高的带宽,而较大的切片尺寸会增加带宽效率(减少传输开销),但会导致压缩较低。结果表明,1460字节的切片结构提高了带宽效率,而不是64个字节的切片结构。

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