Differential equations for multimodal and multispectral color image processing

Multimodal and multispectral color image processing integrates images from different modalities or wavelengths to provide a more detailed and comprehensive analysis. This approach enhances image quality by combining diverse statistical bases. However, it can be computationally intensive and complex, requiring alignment and processing of various data formats, which may lead to challenges in maintaining consistent quality. To address the limitation, this study proposed a novel quaternion differential equation (QDE) for multimodal and multispectral color image processing. The proposed QDE streamlined the integration and alignment of multimodal and multispectral color images using a unified mathematical approach. The data preparation was used to process the multimodal and multispectral color images. Utilizing the quality metrics MSSIM called multiscale structural similarity (0.792), peak signal-to-noise ratio denoted as PSNR (17.732), RMSE or root mean score (0.11) to process the images. The effectiveness of the proposed method is better than others. QDE streamlines the process of multimodal and multispectral color images, resulting in more accurate and high-quality image processing.