基于Hess矩陣的多聚焦圖像融合方法
doi: 10.11999/JEIT170497 cstr: 32379.14.JEIT170497
基金項目:
國家自然科學基金(61572092, U1401252)，國家重點研發(fā)計劃(2016YFC1000307-3)
Multi-focus Image Fusion Based on Hess Matrix
Funds:
The National Natural Science Foundation of China (61572092, U1401252), The National Science and Technology Major Project (2016YFC1000307-3)
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摘要: 該文提出了一種基于Hess矩陣的多聚焦圖像融合方法。該方法利用多尺度下的Hess矩陣檢測特征和背景區(qū)域，并在此基礎(chǔ)上，將源圖像分成特征區(qū)域與非特征區(qū)域，分別采用不同的融合策略生成決策圖；然后通過結(jié)合不同部分的決策圖，得到初始決策圖；最后采用后處理方法對初始決策圖進行精化，得到最終的融合圖像。為了提高融合效果，該文還提出了一種基于多尺度Hess矩陣的聚焦評價方法。同時引入積分圖像進行快速計算，以滿足實時性要求。實驗結(jié)果表明，該方法在主觀視覺感知和客觀評價指標方面都要略優(yōu)于現(xiàn)有的方法。Abstract: This paper proposes a Hess (also known as Hessian) matrix-based multi-focus image fusion method. In this method, multi-scale Hess matrix is utilized to detect feature and background regions. On this basis, source images are split into two different parts, and different fusion strategies are applied to generating decision map respectively. By combining decision maps in different parts, an initial decision map is obtained, and then the initial decision map is refined with post-processing method. To improve the performance of the fusion method, a new focus measure is proposed based on multi-scale Hess matrix for both feature and background regions. Integral images are also introduced for fast computation to meet the real-time application requirements. Experimental results demonstrate that the proposed method is competitive with or even outperforms the state-of-the-art methods in terms of both subjective visual perception and objective evaluation metrics.
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Key words:
- Multi-focus image fusion /
- Hess matrix /
- Integral images
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