• Journal of the Korea Academia-Industrial cooperation Society
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• v.5 no.1
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• pp.38-43
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• 2004

We designed and implemented a medical image query system, including a relational database and DBMS (database management system), which can visualize image data and can achieve spatial, attribute, and mixed queries. Image data used in querying can be visualized in slice, MPR(multi-planner reformat), volume rendering, and overlapping on the query system. To reduce spatial cost and processing time in the system. brain images are spatially clustered, by an adaptive Hilbert curve filling, encoded, and stored to its database without loss for spatial query. Because the query is often applied to small image regions of interest(ROI's), the technique provides higher compression rate and less processing time in the cases.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.648-650
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• 2003

Efficient multi-resolution image fusion aims to take advantage of the high spectral resolution of Landsat TM images and high spatial resolution of SPOT panchromatic images simultaneously. This paper presents a multi-resolution data fusion scheme, based on multirate image representation. Motivated by analytical results obtained from high-resolution multispectral image data analysis: the energy packing the spectral features are distributed in the lower frequency bands, and the spatial features, edges, are distributed in the higher frequency bands. This allows to spatially enhancing the multispectral images, by adding the high-resolution spatial features to them, by a multirate filtering procedure. The proposed method is compared with some conventional methods. Results show it preserves more spectral features with less spatial distortion.

• Journal of the Semiconductor & Display Technology
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• v.6 no.2 s.19
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• pp.53-57
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• 2007

In this paper, a new content-based color image retrieval method is proposed, in which both the color content and the spatial relationship of image have been taken into account. In order to represent the spatial distribution information of image, a disorder matrix, which has the invariance to the rotation and translation of the image content, has been designed. This is based on multi-resolution color-spatial information. We present our algorithm in the following section, and then verified the search results with comparison to other methods, such as color histogram, wavelet histogram, correlogram and wavelet correlogram. Experimental results with various types of images show that the proposed method not only achieves a high image retrieval performance but also improve the retrieval precision.

• Journal of Korean Society for Geospatial Information Science
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• v.16 no.3
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• pp.15-20
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• 2008

High-spatial resolution remote sensing satellites (IKONOS-2, QuickBird and KOMPSAT-2) have provided low-spatial resolution multispectral images and high-spatial resolution panchromatic images. Image fusion or Pan-sharpening is a very important in that it aims at using a satellite image with various applications such as visualization and feature extraction through combining images that have a different spectral and spatial resolution. Many image fusion algorithms are proposed, most methods could not preserve the spectral information of original multispectral image after image fusion. In order to solve this problem, modified induction technique which reduce the spectral distortion of fused image is developed. The spectral distortion is adjusted by the comparison between the spatially degraded pan-sharpened image and original multispectral image and our algorithm is evaluated by QuickBird satellite imagery. In the experiment, pan-sharpened image by various methods can reduce spectral distortion when our algorithm is applied to the fused images.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.6
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• pp.117-124
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• 2008

The approaches to overcome the limited spatial resolution and the limited dynamic range of image sensors have been studied independently. A high resolution image is reconstructed from multiple low resolution observations and a wide dynamic range image is reconstructed from differently exposed multiple low dynamic range in es based on signal processing approach. In practical situations, it is reasonable to address them in a unified context because the recorded image suffers from limitations of both spatial resolution and dynamic range. In this paper, the image acquisition process including limited spatial resolution and limited dynamic range is modelled. With the image acquisition model, the response function of the imaging system is estimated and the single image of which spatial resolution and dynamic range are simultaneously enhanced is obtained. Experimental results indicate that the proposed algorithm outperforms the conventional approaches that perform the high resolution and wide dynamic range reconstruction sequentially with respect to both objective and subjective criteria.

• Proceedings of the KSRS Conference
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• 1998.09a
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• pp.213-217
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• 1998

This study overviews existing evaluation methods of classification accuracy using confusion matrix proposed by Cohen in 1960's, and proposes ISDd(Index of Spatial Distribution by distance) and ISDs(Index of Spatial Distribution by scatteredness) for the evaluation of spatial distribution of satellite image classification errors, which has not been tried yet. Index of spatial distribution offers the basis of decision on adoption/rejection of classification results at sub-image level by evaluation of distribution, such as status of local aggregation of misclassified pixels. So, users can understand the spatial distribution of misclassified pixels and, can have the basis of judgement of suitability and reliability of classification results.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.59-64
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• 2002

This paper presents a method for line segment extraction for 3-d building reconstruction. Building roofs are described as a set of planar polygonal patches, each of which is extracted by watershed-based image segmentation, line segment matching and coplanar grouping. Coplanar grouping and polygonal patch formation are performed per region by selecting 3-d line segments that are matched using epipolar geometry and flight information. The algorithm has been applied to high resolution aerial images and the results show accurate 3-d building reconstruction.

• Korean Journal of Remote Sensing
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• v.24 no.3
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• pp.251-256
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• 2008

Morphing method, one of classic image processing algorithms, has been used in various application fields. The motivation of this work is to investigate its applicability in consideration to geo-spatial data including airborne or space-borne images. For this purpose, the Beier and Neely morphing algorithm is tentatively implemented in the form of a prototype with user interface. As the results, this feature-based morphing with paired image sets can be used for general users: image simulation using two or more images and construction of color-blending image between source image and destination image in different types. Some simple application cases were demonstrated. This scheme is the simple and useful approach for those who want to utilize both geo-spatial data sets and airborne/space-borne image sets.

• Korean Journal of Remote Sensing
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• v.19 no.3
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• pp.247-253
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• 2003

The mainly used technique to correct satellite images with geometric distortion is to develop a mathematical relationship between pixels on the image and corresponding points on the ground. Polynomial models with various transformations have been designed for defining the relationship between two coordinate systems. GCP based geometric correction has peformed overall plane to plane mapping. In the overall plane mapping, overall structure of a scene is considered, but local variation is discarded. The Region with highly variant height is rectified with distortion on overall plane mapping. To consider locally variable region in satellite image, TIN-based rectification on a satellite image is proposed in this paper. This paper describes the relationship between GCP distribution and rectification model through experimental result and analysis about each rectification model. We can choose a geometric correction model as the structural characteristic of a satellite image and the acquired GCP distribution.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.1317-1320
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• 1993

We are concerned with developing a robust method for comprehensive scene analysis. In particular, we address the problem of representing spatial relations between regions in a segmented 2D image. Spatial relations are modeled as fuzzy sets. The method has two aspects, symbolic and quantitative, consisting of assigning labels for spatial relations and numeric degrees to which a relation holds respectively. The procedure of deriving a spatial relation is hierarchical taking into account geometric/physical characteristics of the regions in question.