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Logic Mind Technologies
Vijayangar (Near Maruthi Medicals), Bangalore-40
Ph: 8123668124 // 8123668066
Title: Joint Super Resolution and Denoising
From a Single Depth Image
Abstract—This paper describes a new algorithm for depth image super resolution
and denoising using a single depth image as input. A robust coupled dictionary
learning method with locality coordinate constraints is introduced to reconstruct
the corresponding high resolution depth map. The local constraints effectively
reduce the prediction uncertainty and prevent the dictionary from over-fitting. We
also incorporate an adaptively regularized shock filter to simultaneously reduce the
jagged noise and sharpen the edges. Furthermore, a joint reconstruction and
smoothing framework is proposed with an L0 gradient smooth constraint, making
the reconstruction more robust to noise. Experimental results demonstrate the
effectiveness of our proposed algorithm compared to previously reported methods.
.
Software & Hardware requirement:
1. Hardware requirement:
1. PC
2. RAM minimum 2GB
3. HDD minimum 100GB
2. Software requirement:
1. MATLAB 7.0
2. Signal processing toolbox
3. Image processing toolbox
4. Mathematical toolbox
PROJECT FLOW:
First Review:
Literature Survey
Paper Explanation
Design of Project
Project Enhancement explanation
Second Review:
Implementing 40% of Base Paper
Third Review
Implementing Remaining 60% of Base Paper with Future Enhancement
(Modification)
For More Details please contact
Logic Mind Technologies
Vijayangar (Near Maruthi Medicals), Bangalore-40
Ph: 8123668124 // 8123668066
Mail: logicmindtech@gmail.com

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Joint super resolution and denoising from a single depth image

  • 1. Logic Mind Technologies Vijayangar (Near Maruthi Medicals), Bangalore-40 Ph: 8123668124 // 8123668066 Title: Joint Super Resolution and Denoising From a Single Depth Image Abstract—This paper describes a new algorithm for depth image super resolution and denoising using a single depth image as input. A robust coupled dictionary learning method with locality coordinate constraints is introduced to reconstruct the corresponding high resolution depth map. The local constraints effectively reduce the prediction uncertainty and prevent the dictionary from over-fitting. We also incorporate an adaptively regularized shock filter to simultaneously reduce the jagged noise and sharpen the edges. Furthermore, a joint reconstruction and smoothing framework is proposed with an L0 gradient smooth constraint, making the reconstruction more robust to noise. Experimental results demonstrate the effectiveness of our proposed algorithm compared to previously reported methods. .
  • 2. Software & Hardware requirement: 1. Hardware requirement: 1. PC 2. RAM minimum 2GB 3. HDD minimum 100GB 2. Software requirement: 1. MATLAB 7.0 2. Signal processing toolbox 3. Image processing toolbox 4. Mathematical toolbox PROJECT FLOW: First Review: Literature Survey Paper Explanation Design of Project Project Enhancement explanation Second Review: Implementing 40% of Base Paper Third Review Implementing Remaining 60% of Base Paper with Future Enhancement (Modification) For More Details please contact Logic Mind Technologies Vijayangar (Near Maruthi Medicals), Bangalore-40 Ph: 8123668124 // 8123668066 Mail: logicmindtech@gmail.com