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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 four-camera multispectral mapping system.
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sensors-15-17453-f001: The four-camera multispectral mapping system.

Mentions: With the rapid development of unmanned aerial vehicle (UAV) technology, we urgently need a low cost multispectral system which can acquire multispectral images at the wavelengths based on actual requirements. Our research group developed an airborne high resolution multispectral system (Figure 1) which is mainly composed of a set of digital video recorders (DVR), a ruggedized Getac B300 PC, four identical Hitachi KPF120CL monochrome cameras (2/3 inch Interline type, Progressive Scan CCD), and four bandpass filters. The four identical monochrome cameras are sensitive in the 400 to 1000 nm spectral range, have the capability of obtaining 8-bit images with 1392 × 1040 pixels, and are respectively equipped with near-infrared (800 nm), red (650 nm), green (550 nm) and blue (450 nm) bandpass filters. As a result, it has the flexibility to change filters to acquire other band images in the 400 to 1000 nm spectral range for specific requirements. Because the four cameras are independent, it has the advantage that each camera can be individually adjusted for optimum focus and aperture setting. However, for the multiple optical systems, it is nearly impossible to align different band images taken by the cameras at one exposal optically or mechanically [1], so a registration method is needed.


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 four-camera multispectral mapping system.
© Copyright Policy
Related In: Results  -  Collection

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

sensors-15-17453-f001: The four-camera multispectral mapping system.
Mentions: With the rapid development of unmanned aerial vehicle (UAV) technology, we urgently need a low cost multispectral system which can acquire multispectral images at the wavelengths based on actual requirements. Our research group developed an airborne high resolution multispectral system (Figure 1) which is mainly composed of a set of digital video recorders (DVR), a ruggedized Getac B300 PC, four identical Hitachi KPF120CL monochrome cameras (2/3 inch Interline type, Progressive Scan CCD), and four bandpass filters. The four identical monochrome cameras are sensitive in the 400 to 1000 nm spectral range, have the capability of obtaining 8-bit images with 1392 × 1040 pixels, and are respectively equipped with near-infrared (800 nm), red (650 nm), green (550 nm) and blue (450 nm) bandpass filters. As a result, it has the flexibility to change filters to acquire other band images in the 400 to 1000 nm spectral range for specific requirements. Because the four cameras are independent, it has the advantage that each camera can be individually adjusted for optimum focus and aperture setting. However, for the multiple optical systems, it is nearly impossible to align different band images taken by the cameras at one exposal optically or mechanically [1], so a registration method is needed.

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.