SAR (Synthetic Aperture Radar) image change detection method based on Memetic kernel clustering

Abstract

The invention discloses an SAR (Synthetic Aperture Radar) image change detection method based on Memetic kernel clustering; and the SAR image change detection method mainly solves the problems that the conventional algorithm is high in time complexity and easy to fall into a local optimum value, and has bad performance in region consistency and edge retaining. The implementation process of the SAR image change detection method comprises the steps of: (1) inputting two SAR images at different times, and performing median filtering on the two images; (2) computing the logarithmic ratio difference striograph of the two time-phase images subjected to change detection; (3) setting initial conditions; (4) carrying out kernel clustering and computing a fitness function fk; (5) selecting optimal individuals after performing clone and dual mutation operation on current individuals; (6) selecting optimal individuals after performing clone and crossover operation on the optimal individuals obtained in the step (5); (7) selecting a final individual by an elitist strategy; and (8) judging stop conditions, and outputting clustering results if the conditions are satisfied, otherwise returning to the step (4). The SAR image change detection method based on Memetic kernel clustering has the advantages of rapid convergence rate, high detection precision and accuracy in edge retaining, and can be applied to target identification and change detection of the images in the image processing field.

Description

technical field [0001] The invention belongs to the technical field of image processing, and mainly optimizes the kernel clustering fitness function value based on a Memetic local learning algorithm. The method can be used for change detection of images collected at different times. Background technique [0002] Remote sensing image change detection is to study the changes between images of the same scene in different time periods. Image changes mainly detect changes in radiance values ​​and local textures. These changes may be caused by real changes in the image scene, or by changes in illumination angle, atmospheric conditions, sensor accuracy, ground humidity, etc. An important application of image data obtained from airborne and spaceborne SAR is the change detection. [0003] Change detection technology has been widely used in civilian fields such as environmental monitoring, such as land use analysis, forest harvesting monitoring, disaster estimation, etc. Since SAR...

AI Technical Summary

Problems solved by technology

However, the existing optimization methods often take a long time to deal with optimization problems, and are easy to fall into local optimum during the search process. At the same time, for the change detection problem of complex images, there are often shortcomings of inaccurate edge positioning. Affects the performance of area consistency and edge preservation of image change detection

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