PROJECT TITLE :
A Fast Trilateral Filter-Based Adaptive Support Weight Method for Stereo Matching
Adaptive support weight (ASW) strategies represent the state of the art in native stereo matching, whereas the bilateral filter-based ASW method achieves outstanding performance. However, this method fails to resolve the paradox induced by nearby pixels at different disparities but with similar colours. In this paper, we have a tendency to introduce a completely unique trilateral filter (TF)-based mostly ASW methodology that remedies such ambiguities by considering the potential disparity discontinuities through color discontinuity boundaries, i.e., the boundary strength between two pixels, that is measured by a native energy model. We have a tendency to additionally present a recursive TF-based mostly ASW method whose computational complexity is for the value aggregation step, and for boundary detection, where denotes the input image size. This complexity is thus independent of the support window size. The recursive TF-primarily based technique could be a nonlocal cost aggregation strategy. The experimental analysis on the Middlebury benchmark shows that the proposed methodology, whose average error rate is four.ninety five%, outperforms other local ways in terms of accuracy. Equally, the average runtime of the proposed TF-based cost aggregation is roughly 260 ms on a three.four-GHz Inter Core i7 CPU, that is comparable with state-of-the-art potency.
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