A Multiplicative Noise Removal Approach Based on Partial Differential Equation Model

Figure 4

Detail of the denoising medical image with different methods. (a) A slice of an MRI brain image; (b) image with Gaussian white noise of mean 0 and variance 0.01, PSNR=21.0980; (c) denoised with median filter (template: 3 × 3), PSNR=27.3774; (d) denoised with averaging filter (template: 3 × 3), PSNR=27.7701; (e) denoised with Wiener filter (template: 5 × 5), PSNR=27.8061; (f) denoised with TVM (𝜆=0.01, 10 iterations), PSNR=24.9200; (g) results with the original fourth-order PDE model, PSNR=27.6730; (h) denoised (g) with Median filter, PSNR=27.7743; (i) results with the new fourth-order PDE model, PSNR=26.9902; (j) denoised (i) with median filter, PSNR=28.4746.

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