[논문]Automatic Registration between EO and IR Images of KOMPSAT-3A Using Block-based Image Matching

Kang, Hyungseok

doi:10.7780/kjrs.2020.36.4.5

Automatic Registration between EO and IR Images of KOMPSAT-3A Using Block-based Image Matching 원문보기

대한원격탐사학회지 = Korean journal of remote sensing, v.36 no.4, 2020년, pp.545 - 555

Kang, Hyungseok (The 3rd R&D Institute, Agency for Defense Development)

Abstract ▼ AI-Helper

This paper focuses on automatic image registration between EO (Electro-Optical) and IR (InfraRed) satellite images with different spectral properties using block-based approach and simple preprocessing technique to enhance the performance of feature matching. If unpreprocessed EO and IR images from Kompsat-3A satellite were applied to local feature matching algorithms(Scale Invariant Feature Transform, Speed-Up Robust Feature, etc.), image registration algorithm generally failed because of few detected feature points or mismatched pairs despite of many detected feature points. In this paper, we proposed a new image registration method which improved the performance of feature matching with block-based registration process on 9-divided image and pre-processing technique based on adaptive histogram equalization. The proposed method showed better performance than without our proposed technique on visual inspection and I-RMSE. This study can be used for automatic image registration between various images acquired from different sensors.

주제어

표/그림 (9)

그림 Fig. 1. The spectrum of visible and IR wavelength (Courtesy of InfraTec).
그림 Fig. 2. Correction of contrast reversal using pre-processing (Up : EO, Down : IR).
그림 Fig. 3. Dislocated road of manual processing.
그림 Fig. 4. Position of divided images from Eq. (2).
그림 Fig. 5. Division result of preprocessed satellite images (Left : EO, Right : IR).
그림 Fig. 6. Matching results on block (2,2) (Upper : without MSAC, Lower : with MSAC).
그림 Fig. 7. Matching results on block (1,1) (Upper : without MSAC, Lower : with MSAC).
표 Table 1. Result of SIFT feature and MSAC algorithm
그림 Fig. 8. Result of our image registration algorithm.

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문제 정의

This paper is a research on the method of automatic image registration of the KOMPSAT-3A EO and IR images. We proposed a feature based method which produced similar properties for the two input images through the preprocessing and the division of 9 subimages for the purpose of applying SIFT algorithm on them.

제안 방법

The number of pixels of the EO image is 5,850 × 6,090, and the number of pixels of the IR image is 1,840 × 1,810. IR image was transformed with crop and 30 degree rotation to test proposed method on experiments. Although the experiments were performed using satellite images with original resolution, printed IR images were downsampled to 33 m resolution for the security reason.
In this research, it was assumed that the number of matching pairs existed sufficiently, and since the position difference of the sensors on the platform was not large, image matching was performed by calculating the affine transformation matrix between the two images as the following equation (Eq.
Since this study is a block-based method, image registration is possible for the entire image only if true matching pairs exist in all sub-images. As a result of comparing the three methods of SIFT (Lowe, 2004), SURF (Bay et al.
Because matching points were uniformly distributed on the images, image registration could be performed accurately by the block-basedmethod.The experiments showed performance improvement ofimage registration using with lower I-RMSE value and visual inspection. The proposed approach on this paper could be expanded to utilized for image registration between not only satellite EO and IR images but also among other heterogeneous images.
In addition, we also proposed the block-based approach to improve the accuracy of image registration for a wide area and analyzed the results ofthe block-based method through the experiments. The key points of this research are simple preprocessing, which is applied for the EO and IR images, and block-based method to improve the accuracy of image registration.
The proposed approach on this paper could be expanded to utilized for image registration between not only satellite EO and IR images but also among other heterogeneous images.
The purpose of this research is to propose an automatic image registration between the EO and IR images of KOMPSAT-3A satellite using the feature-based method. Our approach attempted to transform the two images with different spectral properties into similar shapes to enhance the performance of feature matching algorithms(Kim, 2017).

대상 데이터

KOMPSAT-3, 3A, 5 satellites are currently operating in Korea, and the target images of this study are KOMPSAT-3AEO images and IR images. It provides multi-spectral(EO), MWIR, and panchromatic images and the resolution of each image is 2.
The images used in the experiment are the EO and IR satellite images of KOMPSAT-3A, the Greater Hobby Area in Houston, USA. The EO image has spatial resolution of 2.
The images used in this study are EO images in the visible region and IR images (Fig. 1). EO image is composed of reflection information in a visible light wavelength, and IR image is composed of temperature information.

이론/모형

RANSAC algorithm is a prediction method that repeatedly finds the optimal solution by randomly sampling the minimum data to determine the coefficients of model among all data. In this study, mismatched pairs were more robustly removed using MSAC (Torr et al., 2000), the variation of RANSAC algorithm. The positions of feature points in the two images are input variables, 1000 iterations and 2-pixel of matching threshold are set to remove mismatching pairs.

후속연구

On the other hand, if matching points are not detected sufficiently in a block or both blocks of the same number do not have common area, the proposed method may have a problem to complete registration as a whole because the block would not be matched accurately. Further research should be continued to improve the versatility ofthe approach by suggesting a solution of the above problem.

참고문헌 (28)

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