文件名称:LBP.rar
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针对传统方法难以可靠估计图像中纹理单一区域像素点视差的问题,将纹理分析应用于立体匹配中,提
出图像分块整体匹配的方法。首先用LBP/C纹理分析方法对图像纹理进行描述 然后进行基于区域生长的扩张检
测,得到纹理单一图像块 最后对图像块进行整体匹配,得到纹理单一区域的稠密视差图。对国际标准图像进行测试,
结果表明该算法能提高纹理单一区域稠密视差图的精度,具有实用价值
,Due to the difficulty of getting disparity of less textured pixels with traditional approach, block matching
algorithm with texture analysis was put forward. First, the images were described by LBP/C texture analysis. Then the
expansion detection based on region growing was performed, and the less textured blocks were acquired. Finally the dense
disparitymap of less textured area was obtained through block matching. The proposed algorithm was tested with the
international standard image data and comparedwith some existing algorithms. The experimental results show that the proposed
algorithm can improve the accuracy of disparitywhen handling less textured areas and can be used in practic
出图像分块整体匹配的方法。首先用LBP/C纹理分析方法对图像纹理进行描述 然后进行基于区域生长的扩张检
测,得到纹理单一图像块 最后对图像块进行整体匹配,得到纹理单一区域的稠密视差图。对国际标准图像进行测试,
结果表明该算法能提高纹理单一区域稠密视差图的精度,具有实用价值
,Due to the difficulty of getting disparity of less textured pixels with traditional approach, block matching
algorithm with texture analysis was put forward. First, the images were described by LBP/C texture analysis. Then the
expansion detection based on region growing was performed, and the less textured blocks were acquired. Finally the dense
disparitymap of less textured area was obtained through block matching. The proposed algorithm was tested with the
international standard image data and comparedwith some existing algorithms. The experimental results show that the proposed
algorithm can improve the accuracy of disparitywhen handling less textured areas and can be used in practic
相关搜索: LBP
disparity matlab
立体匹配
region growing matlab
区域生长
绔嬩綋鍖归厤
stereomatch
dense matching
纹理
视差图
region growing
Block Matching Algorithms
disparity
Texture analysis matlab
dense
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基于LBP_C纹理分析的立体匹配算法.caj
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