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Image Fusion by Image

Blending

Arthur Goshtasby

ri ht t te ni ersit

Image Registration and Fusion Systems

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more images of a scene into a single highly.

Fusion methods: ow- eve p xe - ase

Mid-level (region-based)

High-level (description-based)

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of different images of a scene into a single.

Image 1 Image 2 Combined image

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Im f i n n im l n inproblem

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.domain, find the image

.

2. Cut out theImage domain

area out o

the mostinformative

.

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Selected local areas in images

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.image.

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-

Highest contrast

0

)log(i

iiG ppE Gray-scale

bgrC EEEE Color

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i, i

the center of the ith block, use

N

j j

ii

yxG

yxyxW

1 ),(

,),(

as the blending function, where

22 .

2exp),( 2

iii yxG

.

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=

1) the image domain is subdivided intoN

,

2) for blocki, the most informative image is

i.k , ,

the fused image is computed from:

N

kii yxIyxWyxO . ),(),(),(

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,

block size is chosen based on image size.

The blending process does not create

input.

e met o s versat e, t can e use to usevarious types of images.

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Application 1:

Fusion of multi-exposure imagesOptimizing criterion: Entropy

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Images courtesy of Paul Debevec, USC

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Optimizing criterion: Entropy

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r g na mages cour esy o ree ayar, o um a n vers y

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Optimizing criterion: Entropy

Original images courtesy of Max Lyons

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Application 2:

Fusion of multi-focus images

Original

mages

Optimizing criterion:

Fused

image

Contrast

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r g na mages cour esy o mage

Fusion Systems Research

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Originalimages

Fused

ima e

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this method is guaranteed to produce an image withthe highest information content at the desired

resolution.

It can be adapted to image resolution by makingblock size a function of image resolution.

By changing the optimization criterion, the method

can be used to fuse various types of images.

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1. T. Porter and T. Duff, Compositing digital images,ACM SIGGRAPH Computer

Graphics, vol. 18, no. 3, 1984, pp. 253-259.

2. P. Willis, Generalized compositing, ACM SIGGRAPH, 2007, pp. 129-135.

3. A. Goshtasby, Fusion of multi-exposure images,Image and Vision Computing,

vo . , , pp. - .

4. A. Goshtasby, Fusion of multifocus images to maximize image information,

Defense and Security SYmposium, 17-21 April 2006, Orlando, Florida, 2006.. n orma on us on , . .

Nikolov (Eds.), vol. 8, 2007.

6. R. S. Blum and Z. Liu,Multi-sensor Image Fusion and its Applications, CRC

Press 2005.

7. F. Sroubek and J. Flusser, Registration and fusion of blurred images,Intl Conf.

Image Analysis and Recognition, 2004, 124-129.

8. C. Genderen and J. L. van Pohl, Multisensor image fusion in remote sensing:

Concepts, methods and applications,Intl J. Remote Sensing, vol. 19, no. 5, 1998,

pp. 823-854.

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