Efficient Compressive Multi-Focus Image Fusion

• 作者: Bin Yang Chao Yang
• 来源期刊: 电脑和通信(英文)
• 学科: 工学
• 关键词: CLARITY Measures COMPRESSIVE IMAGING Multi-Focus IMAGE FUSION
• 年，卷（期）: 2014,（9）
• 页码范围: 78-86
• 页数: 9页
• 分类号: TP39

摘要

Two key points of pixel-level multi-focus image fusion are the clarity measure and the pixel coeffi- cients fusion rule. Along with different improvements on these two points, various fusion schemes have been proposed in literatures. However, the traditional clarity measures are not designed for compressive imaging measurements which are maps of source sense with random or likely ran- dom measurements matrix. This paper presents a novel efficient multi-focus image fusion frame- work for compressive imaging sensor network. Here the clarity measure of the raw compressive measurements is not obtained from the random sampling data itself but from the selected Hada- mard coefficients which can also be acquired from compressive imaging system efficiently. Then, the compressive measurements with different images are fused by selecting fusion rule. Finally, the block-based CS which coupled with iterative projection-based reconstruction is used to re- cover the fused image. Experimental results on common used testing data demonstrate the effectiveness of the proposed method.