Paper
24 October 2006 Spatial filtering method for fringe patterns based on gray gradient
Mingzhao Zhang, Boxiong Wang, Xiuzhi Luo, Chao Yu, Baiqing Hu
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Abstract
Traditional spatial filtering methods such as median filtering and mean filtering are widely used to remove additive noise in images. Images smoothed using these methods are inevitably blurred. If images are fringe patterns and filtering mask used is in fixed shape, such as a rectangle of mxn pixels, the structures of the pattern processed may be even deformed. To resolve this problem, a filtering method with varying mask based on gray gradient is proposed. This method makes full use of the feature of fringe patterns in that the gradient of gray level at a pixel is normal to the tangential direction of the fringe there. According to the method, gradient vector at a pixel is calculated first, and then the shape of the filtering mask to be used is determined based on the gradient vector. If its amplitude is smaller than a predefined value, a nxn square mask is used, on the other hand, if its amplitude is larger than the predefined value, a bar mask normal to the vector is used. Finally, the median value or mean value of the pixels in the mask is then achieved as the smoothed value of the pixel. After the same operations are applied to all pixels in the pattern sequentially, the smoothed version of the fringe pattern is achieved. A simulated fringe pattern with noise is smoothed using this method and other filtering methods for comparison, and the result shows that noise in the fringe pattern can be effectively removed and the characteristic details of the fringes can be reserved at the same time.
© (2006) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Mingzhao Zhang, Boxiong Wang, Xiuzhi Luo, Chao Yu, and Baiqing Hu "Spatial filtering method for fringe patterns based on gray gradient", Proc. SPIE 6357, Sixth International Symposium on Instrumentation and Control Technology: Signal Analysis, Measurement Theory, Photo-Electronic Technology, and Artificial Intelligence, 63570F (24 October 2006); https://doi.org/10.1117/12.716737
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KEYWORDS
Fringe analysis

Digital filtering

Image processing

Image filtering

Spatial filters

Evolutionary algorithms

Chaos

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