Digital Image Analysis
System A. Tsuboi System Development Laboratory, Hitachi Ltd. 1099, Ohzenji Tama, Kawasaki, Kanagawa 215, Japan U. Kubo, S. Yamagata Omika Works, Hitachi Ltd. 5-2-1 Omika-cho Hitachi-shi, Ibaraki-ken, 319-12, Japan S. Fukahata Electrical and Control System Division, Hitachi Ltd Nippon Bldg., 6-2, 2-Chome, Ohtemachi, Chiyoda-ku, Tokyo, 100, Japan T. Kato Systems Engineering Division, ditto Introduction The needs for observing and surveying the earth from the space, so called Remote Sensing, have been increasing. In Japan, the Earth Observation Center (EOC), competed in January 1979, has started an all-out observing activity and so Landsat images are easily available. Under these conditions, we have developed the man-machine interactive digital color image analysis system with easy expandability and reducibility. Herein we will explain our digital image analysis system. Our viewpoint in developing the digital color image analysis system There are various ways of how to compose the image analysis system when we think of following characteristics of the image analysis and needs for that.
1 Function of the system The system consists of image input function, visualization function, evaluation function, image operation function, image analysis function, image editing function, image output function and utilities. Fig. 1 denotes the image data processing procedure and system functions. Fig. 2 Hardware System Configuration Main characteristic functions of the system are as follows.
Hardware system configuration is versatile. Fig. 2 denotes the hardware system configuration. Basic system consists of Process Control Computer HIDIC-80 series with high reliability and expandability, console typewriter, image display unit, mini disk unit and magnetic tape unit (or other image input units). Basic system is expandable step by step in response to various users’ objects. 3 Software configuration with easy expandability of functions The software system configuration is taken notice of following points to be expandable of functions.
One input magnification data, then coputer displays a square located on the CRT cursor. Enlarged imagery by cubic convolution method The imagery inside the squre enlarged and displayed on the CRT in stead of raw imagery. Gray Level Enhancement. Gray level histogram belancing. The Gray level histogram of image data inside red loop is balanced. Fig. 3 shows the example of Landsat image data processing. Conclusion In this paper, we represent all digital color image analysis system, which has relized mini computer-array processor complex system with easy expandability and high cost performance and expandable software architecture. From now, we intend to improve better system responding to various needs. References
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