MAN-MADE AREA CHANGE DETECTION BASED ON MASK WITH HJ IMAGE AND TM IMAGE

Abstract. Change detection of man-made area with HJ image and TM image is difficult mostly due to HJ image having less bands and lower spectral response. In this paper, after the image analysis of HJ image and TM image, a new change detection method based on several times mask of HJ image was used to get really changed man-made area. Several times mask was applied here to narrow the detecting object range. Firstly, coarse man-made areas of new HJ image were extracted by support vector machine (SVM) classer in the mask image based on texture and spectral extraction, while old man-made areas were picked up by SVM classer directly in TM original image. Secondly, after algebra change detection between extracted man-made areas of two images, candidate changed areas were used as mask for HJ image again, and then extractions by SVM classer in the mask images were applied to get really changed man-made area. Through these steps, a high accuracy of man-made area change detection between HJ image and TM image could be got, which had been proved by the experience and accuracy analysis.