An algorithm is presented for speckle reduction in time varying images. The algorithm operates in the time domain and is based on a subdivision of the time evolution of each pixel in the image into homogenous zones. The algorithm operates on a finite time window. The intensity evolution in this window is processed individually for each pixel in the image. The restored time evolution is defined as a piecewise linear function with a predefined maximal number of linear segments. The maximal number of segments is a parameter of the algorithm. Dynamic programming has been applied to obtain the piecewise linear function that minimizes the mean square error. For more than one segment the algorithm finds the optimal way to subdivide the time evolution into homogenous zones. Ordinary linear curve regression is used within each homogenous time segment. Several alternatives for temporal filtering based on discontinuity detection are discussed. The proposed algorithm reduces nonstationary speckle and increases the image contrast.
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