Ridgelet transform as a time-frequency and multiresolution analysis tool is more powerful than wavelet analysis in the
signal and image processing domain, especially in image restoration. Due to the difficulty to appraise the sorts of noise
produced by optical imaging equipments inevitably, this paper use independent component analysis to separate the
independent signals from overlapping signals. Then ridgelet transform were applied to decompose it, and use a new
thresholding de-noising approach to remove noise. At last, we reconstructed the image to obtain a restoration image. By
contrast, the efficiency of our method is better than other traditional filtering approaches.
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