Joint Space-Frequency for Saliency Detection in Optical Remote Sensing Images

Most of the existing saliency detection methods are affected by the complex background and weak contrast in remote sensing images (RSIs), which easily leads to confusion between salient object and background. To solve this problem, we present a general space-frequency joint saliency detection method based on spatial contrast analysis (SCA) and adaptive spectrum analysis (ASA). The proposed SCA constructs a spatial distribution function to give higher saliency to bright elements with similar appearance and compact distribution, which can avoid the interference of similar elements in the background. In addition, for the weak contrast-level salient object, an adaptive spectral energy function is proposed in ASA by combining regional dispersion and frequency spectrum characteristic, which can make full use of frequency spectrum and obtains the complete information of salient object. Finally, the SCA and ASA information are fused by a joint optimization module, which is proposed to integrate the saliency of different contrast levels objects; thus, the final saliency maps are obtained. Evaluated on the extended optical remote sensing saliency detection (EORSSD) dataset and our dataset, the proposed method is superior to other five classical methods in RSI saliency detection.