SNR scalable coding of depth maps using contour-centric SHVC enhancement sublayers

Abstract

Being a scalable extension of the High Efficiency Video Coding (HEVC), Scalable High Efficiency Video Coding (SHVC) standard makes it possible to perform scalable encodings. It produces a single binary stream over several layers built from the same video at different scales of resolutions, frequencies, qualities, pixel depths, or color dynamics. However, SHVC is dedicated to the scalable compression of conventional 2D videos whose only component is the texture image, while a compact and highly scalable representation of depth data is also required in several innovative current and future applications. Finalized in February 2015, 3D High Efficiency Video Coding (3D-HEVC) was introduced as a standard dedicated to depth maps compression. But, it does not allow scalable compression of these latter. We are then faced with 3D-HEVC, a standard adapted to depth maps but not scalable, and SHVC, a standard for scalable compression but not adapted to depth maps. In this paper, we aim to propose our custom SHVC in order to handle the signal-to-noise ratio (SNR) scalable compression of depth maps. This codec consists in limiting SNR scalability to sharp depth discontinuities and their neighborhoods. Increasing quantization parameters values are then conditionally used for the quantization of the coding units transform coefficients as we move away from the contours. Our tailored SHVC codec, when compared to the unmodified SHVC and a 3D-HEVC-based state-of-the-art method, significantly improves the distortion vs. rate performance for benchmark depth maps sequences.