A new approach for selective edge enhancement using unsharp masking is presented. This is based on the premise that biological vision and image reproduction share common principles. In the traditional approach the high frequency components of the image are emphasized, adding to the signal a constant fraction of its high-pass filtered version. The presence of a linear high-pass filter makes the system extremely sensitive to noise. In our approach, the high frequencies added to input image are weighted by a topographic map corresponding to visually salient regions, obtained by a neurodynamical model of visual attention. In this way, the unsharp masking algorithm becomes local and adaptive, enhancing differently the edges according to human perception.
Adaptive edge enhancement using a neurodynamical model of visual attention
IEEE International Conference on Image Processing 2005 ; 3 ; III-972
2005-01-01
267229 byte
Conference paper
Electronic Resource
English
Adaptive Edge Enhancement using A Neurodynamical Model of Visual Attention
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