Forskjeller
Her vises forskjeller mellom den valgte versjonen og den nåværende versjonen av dokumentet.
| Begge sider forrige revisjon Forrige revisjon | |||
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tma4205:2017h:downloads [2017-10-12] markug |
tma4205:2017h:downloads [2017-10-12] (nåværende versjon) markug |
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| Linje 9: | Linje 9: | ||
| * Implementation of the numerical gradient: {{ : | * Implementation of the numerical gradient: {{ : | ||
| * Implementation of the numerical divergence: {{ : | * Implementation of the numerical divergence: {{ : | ||
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| + | The code implements the numerical solution of the PDE \(u-\lambda\textrm{div}(a \nabla u) = f\), where \(a\) is some edge indicator function, which is small near edges of the image \(f\), and large in homogeneous regions of \(f\). | ||
| The input for both the CG and PCG implementation should be a colour image, that is, a 3d array of size \(m \times n \times 3\) (the noisy image). The first output is again a 3d array of the same size (the denoised imaged), and the second output is a vector containing the sizes of the residuals in each step (if one is interested in checking how the methods behave). Note that the code won't work on gray scale images! | The input for both the CG and PCG implementation should be a colour image, that is, a 3d array of size \(m \times n \times 3\) (the noisy image). The first output is again a 3d array of the same size (the denoised imaged), and the second output is a vector containing the sizes of the residuals in each step (if one is interested in checking how the methods behave). Note that the code won't work on gray scale images! | ||