Adaptive total variation model for image denoising based on modified orientation information measure
- Resource Type
- Conference
- Authors
- Wu, Chuansheng; Liu, Wen; Guo, Xiaolong
- Source
- 2010 3rd International Congress on Image and Signal Processing Image and Signal Processing (CISP), 2010 3rd International Congress on. 2:616-620 Oct, 2010
- Subject
- Bioengineering
Communication, Networking and Broadcast Technologies
Computing and Processing
Signal Processing and Analysis
Robotics and Control Systems
Components, Circuits, Devices and Systems
Adaptation model
TV
Mathematical model
Noise reduction
Noise
Image denoising
Image edge detection
orientation information measure
total variation
image denoising
- Language
In this article, an adaptive total variation model by selecting the most appropriate generalized coefficient p adaptively based on modified orientation information measure is introduced. The model can keep the balance between noise smoothing and edges preserving adaptively. In the past, the solutions of TV model were based on nonlinear partial differential equations (PDEs) and the resulting algorithms were very complicated. Therefore we present a promoted effective algorithm based on Bregman iterative regularization for solving the adaptive TV minimization problems in image denoising with no involving solving PDEs. Experimental results show that the proposed denoising model and effective algorithm can properly preserve the main information of the original image with fast solving convergence rate, while the PSNR and subjective visual effect of the denoising images are improved significantly.