Remote sensing image enhancement based on singular value decomposition

Abstract

A satellite image enhancement method based on singular value decomposition (SVD) is presented. The proposed method consists mainly of four steps: image decomposition, adjustable contrast enhancement, noise reduction, and image composition. The method decomposes an image into its singular values, from which the luminance information can be obtained using SVD. In turn, adjustable contrast enhancement is applied by changing the singular values, which are controlled by characteristic-based contrast-level parameters. In the noise reduction process, the high-frequency elements, such as noise, are removed using rank approximation. In the final image composition process, the proposed algorithm combines color and luminance components in order to preserve color consistency. Experimental results show that the proposed scheme has less noise than the conventional methods and improves contrast performance while preserving details.