Article ID Journal Published Year Pages File Type
6866552 Neurocomputing 2014 9 Pages PDF
Abstract
The removal of impulse noise is a prerequisite step in image analysis. The classic partial differential equation (PDE) has achieved a great success in suppressing Gaussian noise, but its performance in reducing impulse noise is less satisfactory. The main difficulty arises from finding a nice diffusion function. To tackle this problem, the paper develops a novel diffusion system to suppress impulse noise. The proposed diffusion system consists of two phases. In the first phase, an effective image filter called Clean Pixel Excluder (CPE) is designed to identify clean pixels from the noisy ones. In the second phase, a robust diffusion model is reformulated by developing a novel diffusion tensor to control the smoothing on both direction and strength adaptively. A numerical scheme based on the multi-scale technique is provided. Extensive experiments on both synthetic and real images show that the proposed system achieves a superior performance over several standard methods in terms of noise suppression and detail preservation.
Related Topics
Physical Sciences and Engineering Computer Science Artificial Intelligence
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