3-D Shape Recovery from Image Focus Using Rank Transform

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• 刊名：Lecture Notes in Computer Science
• 出版年：2016
• 出版时间：2016
• 年：2016
• 卷：10073
• 期：1
• 页码：514-523
• 丛书名：Advances in Visual Computing
• ISBN：978-3-319-50832-0
• 卷排序：10073

文摘

Obtaining an accurate and precise depth map is an ultimate goal of 3-D shape recovery. This article proposes a new robust algorithm Rank Transform (RT) for recovering 3-D shape of an object. The rank transform (RT) encodes for each pixel the position of its grey value in the ranking of all the grey values in its neighborhood. Due to its low computational complexity and robustness against noise, it is superior alternative to most of other SFF approaches. The proposed method is experimented using real and synthetic image sequences. The evaluation is gauged on the basis of unimodality and monotonicity of the focus curve. Finally by means of two global statistical metrics Root mean square error (RMSE) and correlation, we show that our method produces – in spite of simplicity- results of competitive quality.