Research Article
New Regularization Models for Image Denoising with a Spatially Dependent Regularization Parameter
Table 1
Summarized results of the comparative experiment.
| | Figure 2(a) | Figure 2(b) | Figure 2(c) | Figure 2(d) |
| ReErr | | | | | Noisy image | 0.1064 | 0.1847 | 0.1913 | 0.1643 | ROF model | 0.0522 | 0.1279 | 0.0784 | 0.0925 | LLT model | 0.0633 | 0.1273 | 0.0807 | 0.0894 | Hybrid model | 0.0509 | 0.1224 | 0.0758 | 0.0879 | Model 1 | 0.0361 | 0.1151 | 0.0751 | 0.0842 | Model 2 | 0.0298 | 0.1132 | 0.0729 | 0.0827 |
| SNR | | | | | Noisy image | 9.00 | 6.43 | 5.49 | 6.42 | ROF model | 15.19 | 9.62 | 13.24 | 11.41 | LLT model | 13.51 | 9.66 | 12.99 | 11.71 | Hybrid model | 15.41 | 10.00 | 13.53 | 11.85 | Model 1 | 18.39 | 10.53 | 13.61 | 12.23 | Model 2 | 20.06 | 10.68 | 13.87 | 12.38 |
| Time | | | | | ROF model | 0.28 | 1.22 | 1.26 | 1.05 | LLT model | 1.33 | 4.63 | 1.73 | 3.06 | Hybrid model | 2.23 | 8.44 | 4.48 | 5.46 | Model 1 | 2.87 | 6.36 | 5.18 | 4.65 | Model 2 | 2.50 | 9.63 | 5.93 | 6.08 |
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