Abstract: Combining fractal area measurement with fractal fitting error, a new algorithm of extended target detection in complex background is proposed. Through analyzing the self-similarity of fractal surface, the fractal feature named area measurement was developed. Using this fractal feature and the characteristic of extended target, potential target regions were detected. Then, the fractal fitting error of every pixel of original image was estimated, and probabilistic relaxation iteration algorithm(PRIA) was utilized to enhance these errors between the natural background and man-made target. Thus, the target was detected by comparing potential target regions and enhanced fractal feature image. Finally, the background conglutinations were eliminated through mathematical morphology operations. The