Remote Sensing Image Content Retrieval Based on Frequency Spectral Energy

Abstract

There are different research and processing methods for Image Content Retrieval. This article is described the retrieval of remote sensing images method, which is based on the image texture features of the Fourier power spectrum. Firstly, a fixed size remote sensing image unit is selected from the remote sensing image, which is converted to a spectral image by FFT, and extract the eigenvalues in the frequency domain to constitute a searchable image eigenvalue database. Secondly, the similarity between the feature and the database features are examined by the Angular Cosine Algorithm. Lastly, similarity of the resulting image are sorted to select the best match. This method converts the remote sensing image into a spectral image, and makes the selection of the eigenvalue more simple. The Angle Cosine similarity detection method with weight is used to make the similarity detection more accurate.