Image Fusion Based on Discrete Cosine Transform with High Compression

The fusion of images is defined as an alignment of important information from diverse sensors using various mathematical models to generate a single compound image. The fusion of images is used for integrating the complementary multi-temporal, multi-view, and multi-sensor information into a single image with improved image quality and by keeping the integrity of essential features. It is considered a vital pre-processing phase for several applications such as robot vision, aerial, satellite imaging, medical imaging, and robot or vehicle guidance. This paper proposed an enhancement image compression algorithm on a discrete cosine transform (DCT). Then it uses the DCT transformation in the remote sensing image fusion domain and a remote sensing image fusion method with an improved proposed algorithm. The method in this paper has an acceptable compromise between enhancing the spatial resolution of the fused image and maintaining the spectral information. Besides, it is shown that there is no need for codec operations when performing image fusion in the compressed domain such as JPEG. This reduces the time to obtain the fused image and effectively suppresses the problem of dealing with blocky image processing; blockage often occurs. Furthermore, the improved algorithm has better spectral retention capability under the premise of more explicit fusion images and is more suitable for applications requiring higher spectral fidelity.