VMD Based Image Quality Enhancement Using Multi Technology Fusion

Abstract

Despite the success of various enhancement techniques used in many bio-medical applications, edge-preservation-based image enhancement remains a limiting factor for image quality and thus the usefulness of these techniques. In this paper, a new enhancement technique combining the variational mode decomposition (VMD) with the Sobel gradient and equalization technique is proposed. The proposed algorithm first decomposes the image into various sub-modes based on their frequency. The low-frequency components are equalized using the conventional equalization technique, whereas the high-frequency components use a traditional filter. Finally, the edge of the original image is added to the processed image for quality assurance. The proposed algorithm has two advantages over the existing approaches by enhancing only the low-frequency components to extract the hidden artefacts and specifically de-noising the high-frequency component. This process not only enhances the contrast, but also preserves the brightness of the image. A comprehensive study was conducted on the experimental results of benchmark test images using different performance measure matrices to quantify the effectiveness of the approach. In terms of both subjective and objective evaluation, the reconstructed image is found to be more accurate and visually pleasing. It also outperforms the state-of-the-art image-fusion methods, especially in terms of PSNR, RMSE, mutual information, and structural similarity.