Image processing method based on aerospace monitoring - A. I. Mitsiukhin; I. I. Pikirenya (Doklady Belorusskogo gosudarstvennogo universiteta informatiki i radioèlektroniki)
The paper considers a digital image processing method that provides efficient transmission, redistribution and storage of aerospace environmental monitoring videographic information. The requirement to increase the monitoring efficiency, if necessary, to carry out regular monitoring of changes in the image field of the observed object is especially relevant when describing spatially aligned sets of images obtained after multi-zone, multi-time and multi-polarization shooting. In many remote sensing applications, the processing efficiency reflects the degree of reduction in the volume of transmitted, described, analyzed and stored videographic information. The computational processing of digital images based on the coordinate survey scheme is presented. The method can be used to perform the procedure for decoding images in order to solve the problem of classifying objects of interest, analyzing images. Such characteristics of binary objects as a spatial boundary and a contour were used as deciphering signs. These features make it possible to describe the shape of an object, its geometric parameters and search for images with specific spatial structures. The processing method is realized by executing efficient algorithms for coding an image on a discrete grid by means of a chain code and spectral coding based on the fast discrete Hartley transform. The result of processing comes down to minimizing the number of such basic computational operations as multiplication, addition, transferring, as well as reducing the time and capacitive complexity of the program, and reducing the redundancy of the initial data. An example of an effective representation and description of a segmented image of an object is given. The proposed method makes it possible to expand the technical capabilities of more efficient transmission and processing of images for solving problems in the field of remote sensing.