MDLatLRR: A Novel Decomposition Method for Infrared and Visible Image Fusion
Image decomposition is crucial for many image processing tasks, as it allows to extract salient features from source images. A good image decomposition method could lead to a better performance, especially in image fusion tasks. We propose a multi level image decomposition method based on latent low rank representation(LatLRR) which is called MDLatLRR. This decomposition method is applicable to many image processing fields. In this paper, we focus on the image fusion task. We build a novel image fusion framework based on MDLatLRR which is used to decompose source images into detail parts(salient features) and base parts. A nuclear norm based fusion strategy is used to fuse the detail parts and the base parts are fused by an averaging strategy. Compared with other state of the art fusion methods, the proposed algorithm exhibits better fusion performance in both subjective and objective evaluation.
IEEE Transactions on Image Processing