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We propose an algorithm for adaptive image segmentation based on human psychovisual phenomena: visual perception-based segmentation. The new method can reliably segment poor quality images with low contrast and low SNRs. Due to its adaptability, it can be applied to a wide range of low quality images with different object sizes. In successful tests with ultrasound and flow field images that are normally difficult to segment, this new method outperforms a conventional texture-based segmentation method as a result of its biological source.