Multifocus Image Fusion Based On Multiresolution And Modified Principal Component Analysis

Multi-focus imaging fusion is a technique that puts together a fully focused object from the partly focused regions of several objects from the same scene. For producing a high quality fused image, negligible aliasing, and the ability to separate positive from negative frequencies characteristics are important. The ringed artifacts, however, were inserted into a fused image because of a lack of negligible aliasing and the ability to separate positive from negative frequencies properties. A multifocus image fusion algorithm is proposed to resolve these issues, in conjunction with multiresolution and modified principal component analysis. In this, two identical multi-focus images are considered, first they are subjected to the multi-resolution and then to the technique of modified principal component analysis. The multiresolution improves essential image features, which are best used in fusion of images, resulting in good image quality. Modified principal component analysis is applied to reduce the dimensionality of an image. The proposed fusion approach has been tested on a numeral of multifocus images and compared to various popular methods of imaging fusion. The experimental results indicate that in subjective performance and objective assessment, the proposed fusion approach could deliver better fusion results.