The application discloses a wave
image matching method based on fusion matching cost, and relates to the field of
stereo matching, and comprises the following steps: S1, left and right eye images of
waves are collected by using binocular cameras to determine a disparity range; S2, the left and right eye images of original
waves collected in the step S1 are preprocessed; S3, a matching cost value of the wave images is obtained by using an improved Census
algorithm; S4, improved Census cost, AD cost and gradient cost are fused to obtain a cost space; S5, a cross-domain is used for
cost aggregation; S6, a winner-takes-all (WTA) strategy is used to calculate the disparity of the wave images; S7, the disparity map in the step S6 is subjected to left-right consistency checking, and is subjected to hole filling and sub-pixel optimization
processing. The application adopts the above method, solves the problem that the disparity map obtained from the wave images is prone to a large number of invalid points and mismatching points, improves the
correctness of wave
stereo matching, and guarantees the matching precision of the depth discontinuous region.