Compressive sensing (CS) has received a lot of interest due to its compression capability and lack of complexity on the sensor side. In this paper, we present a study of three sampling patterns and investigate their performance on CS reconstruction. We then propose a new image fusion algorithm in the compressive domain by using an improved sampling pattern. There are few studies regarding the applicability of CS to image fusion. The main purpose of this work is to explore the properties of compressive measurements through different sampling patterns and their potential use in image fusion. The study demonstrates that CS-based image fusion has a number of perceived advantages in comparison with image fusion in the multiresolution (MR) domain. The simulations show that the proposed CS-based image fusion algorithm provides promising results.
|Translated title of the contribution||Compressive image fusion|
|Title of host publication||15th IEEE International Conference on Image Processing (ICIP 2008), San Diego, USA|
|Publisher||Institute of Electrical and Electronics Engineers (IEEE)|
|Pages||1308 - 1311|
|Number of pages||4|
|Publication status||Published - 12 Oct 2008|