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Project
Sparse representations for restoration and coding of 3D signals (FWOAL639)
The goal of this project is the development of advanced coding and restoration techniques for three-dimensional (3D) signals based on adaptive sparse representations. We treat three types of 3D signals: static volumes, mesh models, and 3D video.3D video technologies that make use of depth information obtained by means of infrared Time-Of-Flight (TOF) sensors will play an important role in future television and video distribution systems.
The resolution and signal-to-noise ratio in the depth channel are limited due to physical characteristics of the acquisition process. There is a strong demand for video processing techniques that can solve these problems. Recent trends show that current performance limits in image and video restoration and compression can largely be improved by using new spatially-adaptive, oriented basis functions or so-called "geometric" multiresolution representations. Efficient sparse representations of 3D meshes using spatially-adaptive oriented basis functions do not exist yet.
One of the goals of this research is to develop such representations in higher dimensions and on arbitrary surfaces and to use these representations for improved restoration and coding. The combination of complementary expertise of the two groups VUB/IRIS (video and 3D mesh coding) and UGent/IPI (statistical modeling and restoration) is ideal for realizing the goals of this research.
The resolution and signal-to-noise ratio in the depth channel are limited due to physical characteristics of the acquisition process. There is a strong demand for video processing techniques that can solve these problems. Recent trends show that current performance limits in image and video restoration and compression can largely be improved by using new spatially-adaptive, oriented basis functions or so-called "geometric" multiresolution representations. Efficient sparse representations of 3D meshes using spatially-adaptive oriented basis functions do not exist yet.
One of the goals of this research is to develop such representations in higher dimensions and on arbitrary surfaces and to use these representations for improved restoration and coding. The combination of complementary expertise of the two groups VUB/IRIS (video and 3D mesh coding) and UGent/IPI (statistical modeling and restoration) is ideal for realizing the goals of this research.
Date:1 Jan 2012 → 31 Dec 2015
Keywords:Low Power Cmos, Numerical Linear Algebra, Digital Image Processing, Image Reconstruction, Embedded System Design, Displays, Audio Processing, Light Detectors, Micro-Electronics Technology, Sige Bicmos Design, Satellite Image Analysis, Medical Image Analysis, Inverse Problems, Telemedicine, JPEGx, Video Compression, Neural Networks, Mine Detection, Vision, Digital Signal Processing, Electronic System Design, Machine Vision, Micro Electronics, Chip Interconnects (Inter / Intra), Cmos Design, Humanitarian Demining, Speech Processing, Mpegx, Light Emitters, Pattern Recognition, Mm-Wave Technology, Robot Vision, Impedance Tomography, Image Compression, Light Modulators, Medical Image Visualization, Opto-Electronics, Motion Estimation And Tracking, Computer Aided Electronic Design, Multispectral Image Analysis, Electronics, Computer Vision, Image Processing, Industrial Visual Inspection, Image Analysis
Disciplines:Electrical and electronic engineering, Mathematical sciences and statistics, (Bio)medical engineering