The ability to automatically find region of interest in images is useful in the area of satellite remote sensing and its applications. The class of algorithms that find any object of interest with non-prior knowledge, tries to detect objects in images that standout, i.e are salient, by virtue of being different from the rest of the image and consequently capture our attention. In this paper the existing methods for extracting region of interest from stationary images are explored and aimed to propose the fast, efficient method for region of interest extraction that outperform the existing methods in terms of accuracy and computational complexity based on the quaternion frequency domain analysis. The framework of the proposed model rapidly generated the saliency map with the application of quaternion Fourier transform. The saliency regions are accurately detected with the levels of decomposition by using Gaussian pyramid algorithm and thresholding. The proposed algorithm reduces the computational complexity of remote sensing image processing by meeting the timing requirement
