Wavelets shrinkage is the most illustrative of wavelets transform for speckle noise reduction. We aim to study the performance of a monogenic wavelet transform to reduce the speckle noise in digital speckle pattern interferometric fringes. The proposed method is implemented on simulated and experimental speckle fringe patterns and its performance is appraised on the basis of peak signal-to-noise ratio (PSNR) and quality index (Q). The ability to reduce the speckle noise by the proposed method is compared with other classical speckle denoising methods. The obtained results corroborate the effectiveness of the proposed method for speckle noise reduction in speckle fringes in terms of PSNR and Q. It is also observed that the method provides better qualitative and quantitative results. Furthermore, the proposed method preserves the edge information of the speckle fringes, a feature that is quantified by the edge preservation index.

A method to measure the temperature of a metal plate is presented using a Riesz transform method and the monogenic signal to extract the optical phase distribution from a fringe pattern from which one can get the unknown temperature. The performance of this method is evaluated by the RFSIM metric obtained from the 2nd-order Riesz transform. A phase distribution with a good accuracy is provided.

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