Precision Enhancement of 3D Surfaces from Multiple Compressed Depth Maps

TL;DR

This paper introduces a method to improve the precision of 3D surface reconstructions by jointly processing multiple compressed depth maps from different viewpoints, reducing quantization distortion.

Contribution

It proposes a novel joint processing approach using a POCS-like iterative method to enhance depth map accuracy beyond traditional compression limits.

Findings

Improved depth map precision through joint processing

Reduction of quantization distortion in depth maps

Enhanced 3D surface quality from multiple compressed views

Abstract

In texture-plus-depth representation of a 3D scene, depth maps from different camera viewpoints are typically lossily compressed via the classical transform coding / coefficient quantization paradigm. In this paper we propose to reduce distortion of the decoded depth maps due to quantization. The key observation is that depth maps from different viewpoints constitute multiple descriptions (MD) of the same 3D scene. Considering the MD jointly, we perform a POCS-like iterative procedure to project a reconstructed signal from one depth map to the other and back, so that the converged depth maps have higher precision than the original quantized versions.