Research and Implementation of Census Stereo Matching Method Based on Feature Information Optimization
Aiming at the problem of poor matching accuracy of traditional Census stereo matching algo-rithm in weak texture and edge areas,we propose a cost calculation method based on feature information optimization,which integrates more difference information into the window to obtain more accurate pixel disparity value.Subsequently,multidirectional path independent line scan optimization was used to calcu-late the aggregation cost to further improve the matching accuracy.In order to obtain better occlusion area matching effect,a disparity optimization method based on difference filling is proposed to identify the oc-clusion pixels and make disparity filling.In order to improve the efficiency of the algorithm,a new algo-rithm operation mode based on the downsampling strategy is proposed to reduce the hardware load by nar-rowing the disparity search range.Finally,the performance test of the improved Census algorithm was conducted with five sets of standard images as input.The results showed that the average mismatching rate was 6.12％,which was 2.45％lower than before the improvement,and the average efficiency of the algo-rithm increased by 17.7％.
stereo matchingCensuscharacteristic information optimizationdownsampling strategy
万方数据
维普
