Efficient Stereo Matching Based on Pervasive Guided Image Filtering

<figure class="figure-group responsive"><div class="sub-figure" id="a"><object data="https://static-preview.hindawi.com/articles/mpe/volume-2019/3128172/figures/3128172.fig.004a.svgz" name="3128172.fig.004a" type="image/svg+xml"></object><div class="fig-label">(a) The effect of parameter  on the weighted average error rate of FCVF [13]</div></div><div class="sub-figure" id="b"><object data="https://static-preview.hindawi.com/articles/mpe/volume-2019/3128172/figures/3128172.fig.004b.svgz" name="3128172.fig.004b" type="image/svg+xml"></object><div class="fig-label">(b) The effect of parameter σ on the weighted average error rate of FIF [21]</div></div><div class="sub-figure" id="c"><object data="https://static-preview.hindawi.com/articles/mpe/volume-2019/3128172/figures/3128172.fig.004c.svgz" name="3128172.fig.004c" type="image/svg+xml"></object><div class="fig-label">(c) The effect of parameter β on the weighted average error rate of the PGIF(N)</div></div></figure>

<p>Effects of parameter values on the weighted average error rate.</p>

Mathematical Problems in Engineering

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Figure 4

Figure 4: Efficient Stereo Matching Based on Pervasive Guided Image Filtering 