眼睛是靈魂之窗，人類透過視覺的辨識功能維持主要的生活能力。影像則是必須清晰度足夠才可以足以被識別。所以影像融合(image fusion)常常被應用在提高影像的清晰度以增加眼睛的辨識能力。
在本篇論文中提出了一個多焦距融合方法，利用拉普拉斯運算可以提高影像銳利度與小波轉換的多重尺寸特性以達到增強影像的清晰度和辨識度的目的。實驗的部份，在測試合成影像的品質都得到滿意的結果，也測試了此方法對於位移(shift)具有一定程度上的容忍度。本方法也適用於多來源影像融合與彩色影像融合。

A scene to be photographed usually includes objects at various distances and this causes the out of focus objects appear blurry. This paper presents a multi-focus image fusion method to solve this problem. It utilizes Laplacian pyramid and discrete wavelet transform to extract important information from two sources images and fuse them into a single image with high spatial and high spectral information. The algorithm has been tested on synthetic images and natural images with satisfactory results. Robustness in a small degree of shift is also tested on the proposed algorithm. The algorithm is illustrated to be applicable to color image fusion and multi-sensor image fusion as well.

目錄
淡江大學論文提要	I
英文提要	II
目錄	III
圖目錄	V
表目錄	VII
第一章	緒論	1
1.1	研究背景、動機與目的	1
1.2	論文架構	3
第二章	相關文獻回顧	4
2.1	常見的融合方法	4
2.2	融合規則	6
2.3	形態影像學	7
2.4	其他改進的融合規則	7
第三章	本研究相關理論基礎	9
3.1	離散小波轉換	9
3.2	高斯金字塔	12
3.3	拉普拉斯金字塔	12
第四章	本研究所提出的融合法	14
4.1	基本流程介紹	14
4.2	離散小波轉換影像融合	15
4.3	拉普拉斯金字塔影像融合	16
4.4	拉普拉斯小波轉換	18
第五章	實驗結果與討論	21
5.1	品質測試	21
5.1.1	峰值信噪比	21
5.1.2	相互資訊	22
5.1.3	實驗	24
5.2	平移容忍度	28
5.2.1	實驗	28
5.3	其他應用測試	31
第六章	結論	39
相關文獻	40
附錄-英文論文	44
圖目錄
圖1影像融合步驟	2
圖2影像融合結果	5
圖3一維轉換	9
圖4二維轉換	9
圖5對影像進行小波轉換的過程。	10
圖6未經過處理的影像	11
圖7小波轉換處理後	11
圖8反小波轉換	11
圖9高斯金字塔	12
圖10拉普拉斯金字塔建構	13
圖11拉普拉斯金字塔反轉	13
圖12拉普拉斯小波轉換流程	15
圖13離散小波轉換影像融合	16
圖14拉普拉斯金字塔影像融合	18
圖15拉普拉斯小波轉換結構	20
圖16品質測試1	26
圖17品質測試2	27
圖18平移一個像素的結果	29
圖19平移兩個像素的結果	29
圖20平移三個像素的結果	30
圖21多來源影像融合測試	32
圖22彩色影像融合流程	32
圖23彩色影像融合測試	33
圖24彩色品質測試1	35
圖25彩色品質測試2	36
圖26實際照片測試1	37
圖27實際照片測試2	38
表目錄
Table 1 圖16的PSNR和MI	25
Table 2 圖17的PSNR和MI	25
Table 3平移一個像素的PSNR測量結果	29
Table 4 平移兩個像素的PSNR測量結果	29
Table 5 平移三個像素的PSNR測量結果	30
Table 6 圖24的PSNR和MI	34
Table 7 圖25的PSNR和MI	34

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