Fuzzy Transform and Least-Squares Fuzzy Transform: Comparison and Application
Tóm tắt
Fuzzy transform is a novel and well-founded soft computing method for reconstruction and denoising of image data. Recently, a least-squares fuzzy transform that combines a fuzzy transform with a least-squares algorithm for function reconstruction has been proposed. However, the least-squares fuzzy transform has a drawback because it uses an estimation process based on the least-squares algorithm, unlike the fuzzy transform that uses the weighted average of the original function over the fuzzy partition. In this paper, we discuss the similarities and differences between fuzzy transform and least-squares fuzzy transform. Simulation results for various image sizes and noisy images show that the fuzzy transform outperforms the least-squares fuzzy transform in terms of image reconstruction and image denoising.
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