Shape from focus using fast discrete curvelet transform

被引：45

作者：

Minhas, Rashid ^{[1
]}

Mohammed, Abdul Adeel ^{[1
]}

Wu, Q. M. Jonathan ^{[1
]}

机构：

[1] Univ Windsor, Dept Elect & Comp Engn, Windsor, ON N9B 3P4, Canada

来源：

PATTERN RECOGNITION | 2011年 / 44卷 / 04期

基金：

加拿大自然科学与工程研究理事会;

关键词：

Shape from focus; Multifocus; Image fusion; Depth map estimation; Curvelet transform; Contrast limited adaptive histogram equalization; IMAGE FUSION; 3-DIMENSIONAL SHAPE; RECOVERY;

D O I：

10.1016/j.patcog.2010.10.015

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

A new method for focus measure computation is proposed to reconstruct 3D shape using image sequence acquired under varying focus plane. Adaptive histogram equalization is applied to enhance varying contrast across different image regions for better detection of sharp intensity variations. Fast discrete curvelet transform (FDCT) is employed for enhanced representation of singularities along curves in an input image followed by noise removal using bivariate shrinkage scheme based on locally estimated variance. The FDCT coefficients with high activity are exploited to detect high frequency variations of pixel intensities in a sequence of images. Finally, focus measure is computed utilizing neighborhood support of these coefficients to reconstruct the shape and a well-focused image of the scene being probed. (C) 2010 Elsevier Ltd. All rights reserved.

引用

页码：839 / 853

页数：15

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