A Fast Depth-Map Generation Algorithm based on Motion Search from 2D Video Contents

Abstract

Generation of a depth-map from 2D video is the kernel of DIBR (Depth Image Based Rendering) in 2D-3D video conversion systems. However it occupies over most of the system resource where the motion search module takes up 90% time-consuming in typical motion estimation-based depth-map generation algorithms. In order to reduce the computational complexity, in this paper a new fast depth-map generation algorithm based on motion search is developed, in which a fast diamond search algorithm is adopted to decide whether a 16x16 or 4x4 block size is used based on Sobel operator in the motion search module to obtain a sub-depth-map. Then the sub-depth-map will be fused with the sub-depth-maps gotten from depth from color component Cr and depth from linear perspective modules to compensate and refine detail of the depth-map, finally obtain a better depth-map. The simulation results demonstrate that the new approach can greatly reduce over 50% computational complexity compared to other existing methods.

The Infrared Auroral Footprint Tracks of Io, Europa and Ganymede at Jupiter Observed by Juno‐JIRAM

“…We survey the observations performed since PJ1 on 27 August 2016 until PJ42 on 23 May 2022. To determine the position of the emissions, we used a 2D peak‐finder routine (Natan, 2021). For the MAW spots, we gathered 259 images for Io, 127 for Europa and 234 for Ganymede.…”