• Proceedings of the IEEK Conference
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• 2000.09a
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• pp.671-674
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• 2000

In this paper, we present a robust global registration algorithm for multi-frame image mosaics. When we perform a pair-wise registration recovering a projective transformation between two consecutive frames, severe mis-registration among multiple frames, which are not consecutive, can be detected. It is because the concatenation of those pair-wise transformations leads to global alignment errors. To overcome those mis-registrations, we propose a new algorithm using multiple frames for constructing image mosaics. We use a graph to represent the temporal and spatial connectivity and show that global registration can be obtained through the search for an optimal path in the constructed graph. The definition of an adequate objective function characterizing the global registration provides a direct manipulation of the graph. In the presence of moving objects, especially large ones compared with low texture backgrounds, by using the likelihood ratio as the objective function, we can deal with some of the most challenging videos like basketball or soccer Moreover, the algorithm can be parallelized so it can be more efficiently implemented. Finally, we give some experimental results from real videos.

• Journal of Korea Multimedia Society
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• v.18 no.6
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• pp.701-709
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• 2015

Image stitching method is a technique for obtaining an high-resolution image by combining two or more images. In X-ray image for clinical diagnosis, the size of the imaging region taken by one shot is limited due to the field-of-view of the equipment. Therefore, in order to obtain a high-resolution image including large regions such as a whole body, the synthesis of multiple X-ray images is required. In this paper, we propose a rapid stitching method of digital X-ray images using template-based registration. The proposed algorithm use principal component analysis(PCA) and k-nearest neighborhood(k-NN) to determine the location of input images before performing a template-based matching. After detecting the overlapping position using template-based matching, we synthesize input images by alpha blending. To improve the computational efficiency, reduced images are used for PCA and k-NN analysis. Experimental results showed that our method was more accurate comparing with the previous method with the improvement of the registration speed. Our stitching method could be usefully applied into the stitching of 2D or 3D multiple images.

• Proceedings of the Korean Society of Medical Physics Conference
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• 2002.09a
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• pp.103-105
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• 2002

Whole body stereotactic radiosurgery (WBSRS) technique is believed to be useful for the metastatic lesions as well as relatively small primary tumors in the trunk. Unlike stereotactic radiosurgery to intracranial lesion, inherent limitation on immobilization of whole body makes it difficult to achieve the reliable setup reproducibility. For this reason, it is essential to develop an objective and quantitative method of evaluating setup error for WBSRS. An evaluation technique using image registration has been developed for this purpose. Point pair image registrations with WBSRS frame coordinates were performed between two sets of CT images acquired before each treatment. Positional displacements could be determined by means of volumetric planning target volume (PTV) comparison between the reference and the registered image sets. Twenty eight sets of CT images from 19 WBSRS patients treated in Asan Medical Center have been analyzed by this method for determination of setup random error of each treatment. It is objective and clinically useful to analyze setup error quantitatively by image registration technique with WBSRS frame coordinates.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.29B no.4
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• pp.48-57
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• 1992

This paper addresses the estimation of the shift vector from aerial image sequences. The conventional feature-based and area-based matching methods are simulated for determining the suitable image registration scheme. Computer simulations show that the feature-based matching schemes based on the co-occurrence matrix, autoregressive model, and edge information do not give a reliable matching for aerial image sequences which do not have a suitable statistical model or significant features. In area-based matching methods we try various similarity functions for a matching measure and discuss the factors determining the matching accuracy. To reduce the estimation error of the shift vector we propose the reference window selection scheme. We also discuss the performance of the proposed algorithm based on the simulation results.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.999-1000
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• 2008

Image Registration is used many works in image processing widely. But It is difficult to find the accuracy informations such as translation, rotation, and scaling between images. This paper proposes an algorithm that Fourier based image registration using the pyramid edge detection and line fitting. It can be estimated the informations by each sub-pixels. The proposed algorithm can be used for image registrations which high efficiency is required such as GIS, or MRI, CT, image mosaicing, weather forecasting, etc.

• Journal of the Korean Society for Precision Engineering
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• v.30 no.9
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• pp.991-999
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• 2013

Lower limbs deformity is a congenital disease and can also be occurred by an acquired factor. This paper suggests a new technique for surgical planning of Corrective Osteotomy for Lower Limbs (COLL) using 2D-3D medical image registration. Converting to a 3D modeling data of lower limb based on CT (computed tomography) scan, and divide it into femur, tibia and fibula; which composing the lower limb. By rearranging the model based on the biplane 2D images of X-ray data, a 3D upright bone structure was acquired. There are two ways to array the 3D data on the 2D image: Intensity-based registration and feature-based registration. Even though registering Intensity-based method takes more time, this method will provide more precise results, and will improve the accuracy of surgical planning.

• Journal of the Korea Society of Computer and Information
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• v.17 no.6
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• pp.37-48
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• 2012

Image registration is a process to establish the spatial correspondence between the images of same scene, which are acquired at different view points, at different times, or by different sensors. In this paper, we propose an effective registration method for images acquired by multi-sensors, such as EO (electro-optic) and IR (infrared) sensors. Image registration is achieved by extracting features and finding the correspondence between features in each input images. In the recent research, the multi-sensor image registration method that finds corresponding features by exploiting NMI (Normalized Mutual Information) was proposed. Conventional NMI-based image registration methods assume that the statistical correlation between two images should be global, however images from EO and IR sensors often cannot satisfy this assumption. Therefore the registration performance of conventional method may not be sufficient for some practical applications because of the low accuracy of corresponding feature points. The proposed method improves the accuracy of corresponding feature points by combining the gradient orientation as spatial information along with NMI attributes and provides more accurate and robust registration performance. Representative experimental results prove the effectiveness of the proposed method.

• Proceedings of the Korea Society for Simulation Conference
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• 2003.11a
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• pp.201-206
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• 2003

In clinical practice, CT Angiography is a powerful technique for the visualziation of blood flow in arterial vessels throughout the body. However CT Angiography images of blood vessels anywhere in the body may be fuzzy if the patient moves during the exam. In this paper, we propose a novel technique for removing global motion artifacts in the 3D space. The proposed methods are based on the two key ideas as follows. First, the method involves the extraction of a set of feature points by using a 3D edge detection technique based on image gradient of the mask volume where enhanced vessels cannot be expected to appear, Second, the corresponding set of feature points in the contrast volume are determined by correlation-based registration. The proposed method has been successfully applied to pre- and post-contrast CTA brain dataset. Since the registration for motion correction estimates correlation between feature points extracted from skull area in mask and contrast volume, it offers an accelerated technique to accurately visualize blood vessels of the brain.

• Journal of KIISE
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• v.43 no.9
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• pp.1034-1042
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• 2016

Together with machine-learning frameworks, area-based imagery registration techniques can be easily applied to diverse types of image pairs without predefined features and feature descriptors. However, feature detectors are often used to quickly identify candidate image patch pairs, limiting the applicability of these registration techniques. In this paper, we propose a ConvNet (Convolutional Network) "Dart" that provides not only the matching metric between patches, but also information about their distance, which are helpful in reducing the search space of the corresponding patch pairs. In addition, we propose a ConvNet "Fad" to identify the patches that are difficult for Dart to improve the accuracy of registration. These two networks were successfully implemented using Deep Learning with the help of a number of training instances generated from a few registered image pairs, and were successfully applied to solve a simple image registration problem, suggesting that this line of research is promising.

• Korean Journal of Remote Sensing
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• v.38 no.6_4
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• pp.1901-1910
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• 2022

Arriving in the new space age, securing technology for fusion application of KOMPSAT-3·3A and global satellite images is becoming more important. In general, multi-sensor satellite images have relative geometric errors due to various external factors at the time of acquisition, degrading the quality of the satellite image outputs. Therefore, we propose a fine-image registration methodology to minimize the relative geometric error between KOMPSAT-3·3A and global satellite images. After selecting the overlapping area between the KOMPSAT-3·3A and foreign satellite images, the spatial resolution between the two images is unified. Subsequently, tie-points are extracted using a hybrid matching method in which feature- and area-based matching methods are combined. Then, fine-image registration is performed through iterative registration based on pyramid images. To evaluate the performance and accuracy of the proposed method, we used KOMPSAT-3·3A, Sentinel-2A, and PlanetScope satellite images acquired over Daejeon city, South Korea. As a result, the average RMSE of the accuracy of the proposed method was derived as 1.2 and 3.59 pixels in Sentinel-2A and PlanetScope images, respectively. Consequently, it is considered that fine-image registration between multi-sensor satellite images can be effectively performed using the proposed method.