Anisotropic Diffusion for Details Enhancement in Multiexposure Image Fusion

<table class="table-group" width="800px"><tr class="fig-image" id="a"><td><img alt="928971.fig.003a" src="https://static.hindawi.com/articles/isrn/volume-2013/928971/figures/928971.fig.003a.jpg"/></td></tr><tr class="fig-caption"><td align="center"><table><tr><td><b>(a) </b>  1D structure</td></tr></table></td></tr><tr class="fig-image" id="b"><td><img alt="928971.fig.003b" src="https://static.hindawi.com/articles/isrn/volume-2013/928971/figures/928971.fig.003b.jpg"/></td></tr><tr class="fig-caption"><td align="center"><table><tr><td><b>(b) </b> 2D structure</td></tr></table></td></tr></table>

<table>Gradient computation. (a) One-dimensional (1D) grid structure: the signal flow is calculated between two neighboring nodes (solid connection). (b) Two-dimensional (2D) grid structure: the signal flow is calculated between four neighboring nodes (solid connection).</table>

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Figure 3

Figure 3: Anisotropic Diffusion for Details Enhancement in Multiexposure Image Fusion 