Exploiting color-depth image correlation to improve depth map compression

R. Farrugia, Isabel Gambin
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引用次数: 2

Abstract

The multimedia signal processing community has recently identified the need to design depth map compression algorithms which preserve depth discontinuities in order to improve the rendering quality of virtual views for Free Viewpoint Video (FVV) services. This paper adopts contour detection with surround suppression on the color video to approximate the foreground edges present in the depth image. Displacement estimation and compensation is then used to improve this prediction and reduce the amount of side information required by the decoder. Simulation results indicate that the proposed method manages to accurately predict around 64% of the blocks. Moreover, the proposed scheme achieves a Peak Signal-to-Noise Ratio (PSNR) gain of around 4.9-6.6 dB relative to the JPEG standard and manages to outperform other state of the art depth map compression algorithms found in literature.
利用彩色深度图像相关来改善深度图压缩
为了提高免费视点视频(FVV)服务的虚拟视图的渲染质量,多媒体信号处理界最近已经确定需要设计深度图压缩算法来保留深度不连续。本文在彩色视频中采用带环绕抑制的轮廓检测来逼近深度图像中存在的前景边缘。然后使用位移估计和补偿来改进这种预测并减少解码器所需的侧信息量。仿真结果表明,该方法能够准确预测约64%的区块。此外,与JPEG标准相比,该方案实现了约4.9-6.6 dB的峰值信噪比(PSNR)增益,并设法优于文献中发现的其他最先进的深度图压缩算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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