Modified adaptive support weight and disparity search range estimation schemes for stereo matching processors

Recently, to obtain three-dimensional depth information from a set of stereo images, stereo matching processors are widely used in intelligent robots, autonomous vehicles, and the Internet of things environment, all of which require real-time processing capability with minimal hardware resources. In this paper, we propose a modified adaptive support weight scheme with rectangular ring-type window configurations that minimize hardware resources while maintaining matching accuracy. In addition, to reduce the computational overhead of window-based local stereo matching algorithms, we present a robust disparity search range estimation scheme based on stretched depth histograms. To evaluate the performance of the proposed schemes, we implemented them using C language and performed experiments. In addition, to show the feasibility of the hardware implementation of the proposed schemes, we also describe them using Verilog hardware description language and implemented them using a field-programmable gate array-based platform. Experimental results show that compared to conventional method, the proposed schemes reduced up to 57% of hardware resources and 33% of computational overhead, respectively.