• Laser & Optoelectronics Progress
  • Vol. 62, Issue 2, 0215004 (2025)
Jingfa Lei1、2、3、*, Zihan Wei1、2, Yongling Li1、2、3, Ruhai Zhao1、2, and Miao Zhang1、2
Author Affiliations
  • 1School of Mechanical and Electrical Engineering, Anhui Jianzhu University, Hefei 230601, Anhui , China
  • 2Key Laboratory of Intelligent Manufacturing of Construction Machinery, Anhui Education Department, Hefei 230601, Anhui , China
  • 3Sichuan Provincial Key Laboratory of Process Equipment and Control Engineering, Zigong 643000, Sichuan , China
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    DOI: 10.3788/LOP240968 Cite this Article Set citation alerts
    Jingfa Lei, Zihan Wei, Yongling Li, Ruhai Zhao, Miao Zhang. Adaptive Stereo Matching Based on Local Information Entropy and Improved AD-Census Transform[J]. Laser & Optoelectronics Progress, 2025, 62(2): 0215004 Copy Citation Text show less

    Abstract

    To enhance the accuracy of traditional local stereo matching algorithms in weak-texture regions and address the limitations of the AD-Census transform in adapting to local region features during cost fusion, an adaptive stereo matching algorithm based on local information entropy and an improved AD-Census transform is proposed. In the cost calculation stage, the local information entropy of the input image is first computed. Then, based on the entropy of the pixel neighborhood, an adaptive window size is selected to refine the Census transform. Next, an adaptive fusion weight is determined from the local information entropy to combine the improved Census and AD costs. In the cost aggregation stage, a unidirectional dynamic programming aggregation algorithm is introduced. After disparity computation and optimization, the final disparity map is produced. The algorithm is evaluated on the Middlebury platform using standard test images. Experimental results indicate that the proposed algorithm achieves an average mismatch rate of 5.94% in non-occluded areas and 8.37% across all areas, outperforming many existing algorithms in terms of matching quality and robustness to noise.
    Jingfa Lei, Zihan Wei, Yongling Li, Ruhai Zhao, Miao Zhang. Adaptive Stereo Matching Based on Local Information Entropy and Improved AD-Census Transform[J]. Laser & Optoelectronics Progress, 2025, 62(2): 0215004
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