Image segmentation approach for realizing zoomable streaming HEVC video

Abstract

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.