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A Multispectral Image Creating Method for a New Airborne Four-Camera System with Different Bandpass Filters.

Li H, Zhang A, Hu S - Sensors (Basel) (2015)

Bottom Line: For this multispectral system, an automatic multispectral data composing method was proposed.For the difficult registration problem between visible band images and near-infrared band images in cases lacking manmade objects, we presented an effective method based on the structural characteristics of the system.Experiments show that our method can acquire high quality multispectral images and the band-to-band alignment error of the composed multiple spectral images is less than 2.5 pixels.

View Article: PubMed Central - PubMed

Affiliation: Key Laboratory of 3D Information Acquisition and Application of Ministry, Capital Normal University, Beijing 100048, China. lihanlun@126.com.

ABSTRACT
This paper describes an airborne high resolution four-camera multispectral system which mainly consists of four identical monochrome cameras equipped with four interchangeable bandpass filters. For this multispectral system, an automatic multispectral data composing method was proposed. The homography registration model was chosen, and the scale-invariant feature transform (SIFT) and random sample consensus (RANSAC) were used to generate matching points. For the difficult registration problem between visible band images and near-infrared band images in cases lacking manmade objects, we presented an effective method based on the structural characteristics of the system. Experiments show that our method can acquire high quality multispectral images and the band-to-band alignment error of the composed multiple spectral images is less than 2.5 pixels.

No MeSH data available.


The band images with less artificial objects; (a) the infrared band; (b) the red band; (c) the green band; (d) the blue band.
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sensors-15-17453-f006: The band images with less artificial objects; (a) the infrared band; (b) the red band; (c) the green band; (d) the blue band.

Mentions: As shown in Figure 6, there are four different band images acquired by the multispectral system at one exposure. Compared with Figure 4, the four pictures shown in Figure 6 contain fewer artificial objects. The number of SIFT feature points in the four images respectively is 4739, 7964, 7497 and 8999. For the same reason as in Experiment 1, the green band is chosen to be the reference band image, and the other three band images are registered to it. As shown in Table 1, the initial matches (IM) respectively are 1446, 1139, 537, and the correct matches (CM) respectively are 1038, 926, 36; the correct rate (CR) respectively is 72%, 85%, 7%. The correct rate (CR) between the green band and the infrared band is significantly lower than 50%. It is unable to get the correct result using the RANSAC directly, as shown in Figure 7 (left). Because Figure 6 and Figure 4 are from a same flight strip, there is little change in flying height and flying attitude. So, the evaluated (xrow, ycol) in Experiment 1 can be used to eliminate false matches. 398, 185, and 491 false matches have respectively been removed, as shown in Table 1. After eliminating, the matches respectively become 1048, 954, 46, and the correct rates respectively become 99%, 97%, 78% , so the registration performance is significantly improved. All of these are much higher than 50%, making RANSAC more reliable, and solving the registration problem between the green band and infrared band, as shown in Figure 7 (right).


A Multispectral Image Creating Method for a New Airborne Four-Camera System with Different Bandpass Filters.

Li H, Zhang A, Hu S - Sensors (Basel) (2015)

The band images with less artificial objects; (a) the infrared band; (b) the red band; (c) the green band; (d) the blue band.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4541943&req=5

sensors-15-17453-f006: The band images with less artificial objects; (a) the infrared band; (b) the red band; (c) the green band; (d) the blue band.
Mentions: As shown in Figure 6, there are four different band images acquired by the multispectral system at one exposure. Compared with Figure 4, the four pictures shown in Figure 6 contain fewer artificial objects. The number of SIFT feature points in the four images respectively is 4739, 7964, 7497 and 8999. For the same reason as in Experiment 1, the green band is chosen to be the reference band image, and the other three band images are registered to it. As shown in Table 1, the initial matches (IM) respectively are 1446, 1139, 537, and the correct matches (CM) respectively are 1038, 926, 36; the correct rate (CR) respectively is 72%, 85%, 7%. The correct rate (CR) between the green band and the infrared band is significantly lower than 50%. It is unable to get the correct result using the RANSAC directly, as shown in Figure 7 (left). Because Figure 6 and Figure 4 are from a same flight strip, there is little change in flying height and flying attitude. So, the evaluated (xrow, ycol) in Experiment 1 can be used to eliminate false matches. 398, 185, and 491 false matches have respectively been removed, as shown in Table 1. After eliminating, the matches respectively become 1048, 954, 46, and the correct rates respectively become 99%, 97%, 78% , so the registration performance is significantly improved. All of these are much higher than 50%, making RANSAC more reliable, and solving the registration problem between the green band and infrared band, as shown in Figure 7 (right).

Bottom Line: For this multispectral system, an automatic multispectral data composing method was proposed.For the difficult registration problem between visible band images and near-infrared band images in cases lacking manmade objects, we presented an effective method based on the structural characteristics of the system.Experiments show that our method can acquire high quality multispectral images and the band-to-band alignment error of the composed multiple spectral images is less than 2.5 pixels.

View Article: PubMed Central - PubMed

Affiliation: Key Laboratory of 3D Information Acquisition and Application of Ministry, Capital Normal University, Beijing 100048, China. lihanlun@126.com.

ABSTRACT
This paper describes an airborne high resolution four-camera multispectral system which mainly consists of four identical monochrome cameras equipped with four interchangeable bandpass filters. For this multispectral system, an automatic multispectral data composing method was proposed. The homography registration model was chosen, and the scale-invariant feature transform (SIFT) and random sample consensus (RANSAC) were used to generate matching points. For the difficult registration problem between visible band images and near-infrared band images in cases lacking manmade objects, we presented an effective method based on the structural characteristics of the system. Experiments show that our method can acquire high quality multispectral images and the band-to-band alignment error of the composed multiple spectral images is less than 2.5 pixels.

No MeSH data available.