Visual saliency mechanism‐based object recognition with high‐resolution remote‐sensing images

Abstract

Object recognition with remote-sensing image is widely used in many areas. Some objects are smaller and denser in the high-resolution images, such as the oil tank, ship, and aircraft. The recognition of this kind of objects is more difficult than the objects with low-resolution images, for example, bridges and airports. The recognition performance is more dependent on the shallower features. The contour of these objects is obvious, and the characteristics are quite different from background, which satisfies the human visual saliency mechanism. Here, the authors propose a novel theme of object recognition method based on visual saliency mechanism for remote-sensing images with sub-meter resolution. The experimental results show that the proposed method performs best compared with other algorithm.