A low-complexity region-based video coder using backward morphological motion field segmentation

1999 ◽  
Vol 8 (3) ◽  
pp. 332-345 ◽  
Author(s):  
Xuguang Yang ◽  
K. Ramchandran
Keyword(s):  
Low Complexity ◽  
Motion Field ◽  
Video Coder

scholarly journals A SENSOR AIDED H.264/AVC VIDEO ENCODER FOR AERIAL VIDEO SEQUENCES WITH IN THE LOOP METADATA CORRECTION

2015 ◽  
Vol II-3/W5 ◽  
pp. 483-490
Author(s):  
L. Cicala ◽  
C. V. Angelino ◽  
G. Ruatta ◽  
E. Baccaglini ◽  
N. Raimondo
Keyword(s):  
Navigation System ◽  
Low Complexity ◽  
Video Data ◽  
Video Sequences ◽  
Battery Life ◽  
Motion Field ◽  
Still Image ◽  
Coding Systems ◽  
High Resolution Images ◽  
Video Data Compression

Unmanned Aerial Vehicles (UAVs) are often employed to collect high resolution images in order to perform image mosaicking and/or 3D reconstruction. Images are usually stored on board and then processed with on-ground desktop software. In such a way the computational load, and hence the power consumption, is moved on ground, leaving on board only the task of storing data. Such an approach is important in the case of small multi-rotorcraft UAVs because of their low endurance due to the short battery life. Images can be stored on board with either still image or video data compression. Still image system are preferred when low frame rates are involved, because video coding systems are based on motion estimation and compensation algorithms which fail when the motion vectors are significantly long and when the overlapping between subsequent frames is very small. In this scenario, UAVs attitude and position metadata from the Inertial Navigation System (INS) can be employed to estimate global motion parameters without video analysis. A low complexity image analysis can be still performed in order to refine the motion field estimated using only the metadata. In this work, we propose to use this refinement step in order to improve the position and attitude estimation produced by the navigation system in order to maximize the encoder performance. Experiments are performed on both simulated and real world video sequences.

A Low-Complexity Sparse Channel Estimation Method for OFDM Systems

2010 ◽  
Vol E93-B (8) ◽  
pp. 2211-2214
Author(s):  
Bin SHENG ◽  
Pengcheng ZHU ◽  
Xiaohu YOU ◽  
Lan CHEN
Keyword(s):  
Channel Estimation ◽  
Estimation Method ◽  
Low Complexity ◽  
Ofdm Systems ◽  
Sparse Channel Estimation ◽  
Sparse Channel
Sign in / Sign up

Export Citation Format

Share Document