• Korean Journal of Remote Sensing
• /
• v.27 no.6
• /
• pp.717-728
• /
• 2011

An efficient method for the unsupervised classification of high resolution imagery is suggested in this paper. It employs pixel-linking and merging based on the adjacency graph. The proposed algorithm uses the neighbor lines of 8 directions to include information in spatial proximity. Two approaches are suggested to employ neighbor lines in the linking. One is to compute the dissimilarity measure for the pixel-linking using information from the best lines with the smallest non. The other is to select the best directions for the dissimilarity measure by comparing the non-homogeneity of each line in the same direction of two adjacent pixels. The resultant partition of pixel-linking is segmented and classified by the merging based on the regional and spectral adjacency graphs. This study performed extensive experiments using simulation data and a real high resolution data of IKONOS. The experimental results show that the new approach proposed in this study is quite effective to provide segments of high quality for object-based analysis and proper land-cover map for high resolution imagery of urban area.

• 전기의세계
• /
• v.28 no.6
• /
• pp.61-77
• /
• 1979

This paper is concerned with minimization process of the binary logic function. This paper describes an algorithm called the SIMPLE TABLE METHOD that well suited to minimization a switching function of any number of variables. For the Simple Table construction, a theorem based upon the numerical properties of the logic function is derived from the relationships governing minterms of the given function. Finally the minimal sum of products can be obtained in terms of the Direct Method or the Indirect Method from the table and table characteristics derived from the Simple Table. The properties and table characteristics used in this paper are described. All the minterms of a switching function are manipulated only by decimal numbers, not binary numbers. Some examples are used as a vehicle to guide the readers who are familiar with the Karnaugh map and Quine-McCluskey tabular method to this New method. These examples not only treat how to handle Don't Care miterms but also show the multiple output functions.

• 전기의세계
• /
• v.30 no.2
• /
• pp.101-111
• /
• 1981

This paper describes two methods which generate all the prime implicants (PI's) quickly by using the directions of adjacency tavle (DA-table) that gives the knowledge of adjacency relations among the given minterms. One is a graphical method that enables us to generate PI's by hand, the other is a checking method that determines the existance of PI's quickly when it is programmed on a digital computer. And a fast minimization algorithm will be shown in this paper that can be implemented with reduced computational effort by selecting essential prime implicants (EPI's) first of all and using the concept of the integration of the PI identification and selection procedure. The procedure, proposed in this paper, has all the advantage of Karnaugh mapping, so the procedure is simple and easy.

• Korean Journal of Remote Sensing
• /
• v.30 no.6
• /
• pp.817-827
• /
• 2014

In the satellite remote sensing, the operational environment of the satellite sensor causes image degradation during the image acquisition. The degradation results in noise and blurring which badly affect identification and extraction of useful information in image data. This study proposes a maximum a posteriori (MAP) estimation using Point-Jacobian iteration to restore a degraded image. The proposed method assumes a Gaussian additive noise and Markov random field of spatial continuity. The proposed method employs a neighbor window of spoke type which is composed of 8 line windows at the 8 directions, and a boundary adjacency measure of Mahalanobis square distance between center and neighbor pixels. For the evaluation of the proposed method, a pixel-wise classification was used for simulation data using various patterns similar to the structure exhibited in high resolution imagery and an unsupervised segmentation for the remotely-sensed image data of 1 mspatial resolution observed over the north area of Anyang in Korean peninsula. The experimental results imply that it can improve analytical accuracy in the application of remote sensing high resolution imagery.

• Journal of Korean Society for Geospatial Information Science
• /
• v.21 no.2
• /
• pp.93-98
• /
• 2013

Multi-temporal high resolution satellite images are essential data for efficient city analysis and monitoring. Yet even when acquired from the same location, identical sensors as well as different sensors, these multi-temporal images have a geometric inconsistency. Matching points between images, therefore, must be extracted to match the images. With images of an urban area, however, it is difficult to extract matching points accurately because buildings, trees, bridges, and other artificial objects cause shadows over a wide area, which have different intensities and directions in multi-temporal images. In this study, we analyze a shadow effect on image matching of high resolution satellite images in urban area using Scale-Invariant Feature Transform(SIFT), the representative matching points extraction method, and automatic shadow extraction method. The shadow segments are extracted using spatial and spectral attributes derived from the image segmentation. Also, we consider information of shadow adjacency with the building edge buffer. SIFT matching points extracted from shadow segments are eliminated from matching point pairs and then image matching is performed. Finally, we evaluate the quality of matching points and image matching results, visually and quantitatively, for the analysis of shadow effect on image matching of high resolution satellite image.