Adaptive sparse representation of depth maps targeting view synthesis quality

Completely embedded in the 3D era, depth maps coding becomes a must in order to favor 3D admission to different fields of application, ranging from video games to medical imaging. This paper presents a novel depth coding approach that decomposes a decimated version of the original depth image on a sparse set of coefficients and mixed discrete cosine and B-splines atoms. The upstream decimation step reduces encoding bitrate without significant loss of virtual views quality. Depth decomposition is performed through minimization of an adaptive Rate/Distortion cost function, where we manipulate its weight parameter according to depth discontinuities. We then refine the choice of distortion metric in order to quantify the effect of depth maps coding on rendered views quality. Experiments show the relevance of the proposed method, able to obtain considerable tradeoffs between bitrate and synthesized views distortion.