1 January 1995 Use of interferometric directionality for noise reduction [also Letter 34(7)2168(Jul1995)]
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Abstract
Accurate static fringe-pattern analysis is very important for the successful application of a variety of interferometric techniques. In most cases of practical application, especially in aerodynamic flow testing, substantial noise can be introduced due to prevailing adverse environments. A means for efficiently reducing interferometric noise is thus desirable. Conventional noise reduction has mostly depended on ordinary averaging or median filtering in a squared mask to remove high-frequency components. These techniques, however, can induce some side effects of image blurring. If the structural integrity needs to be preserved, the method to be adopted should be able to eliminate noise efficiently without altering local intensity gradients, that is, local contrasts. In this paper, the concept of directional smoothing is introduced and its application to interferometric noise reduction is presented. Interferograms provide locally similar fringe directions, that is, isophase lines contaminated by noise, and thus contain directional information. In essence, the method exploits this valuable fringe directionality by setting up a slender mask of large aspect ratio along a fringe. A new value, that is, the average or median intensity of the mask, is then assigned to each pixel. The mask can be straight or curved. For a straight mask, the average direction of fringes within a processing region is employed. A curved mask is made to conform to a fringe curve. The proposed method is tested by computer simulation of experiments as well as with real interferograms. The results appear to be promising as compared with conventional techniques, especially for high-level noise.
Enxi Yu, Soyoung Stephen Cha, and Wonjong Joo "Use of interferometric directionality for noise reduction [also Letter 34(7)2168(Jul1995)]," Optical Engineering 34(1), (1 January 1995). https://doi.org/10.1117/12.183990
Published: 1 January 1995
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Cited by 5 scholarly publications.
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KEYWORDS
Denoising

Interferometry

Digital filtering

Image processing

Edge detection

Image filtering

Computer simulations

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