Multi focus image fusion using image enhancement techniques with wavelet transformation

Abstract

Multi-focus image fusion produces a unification of multiple images having different areas in focus, which contain necessary and detailed information in the individual image. The paper is proposing a novel idea in a pre-processing step in the image fusion environment in which sharpening techniques applied before fusion in the pre-processing step. This article is proposing multi-focus hybrid techniques for fusion, based on image enhancement, which helps to identify the key features and minor details and then fusion performed on the enhanced images. In image enhancement, we introduced a new hybrid sharpening method that combines Laplacian Filter (LF) with a Discrete Fourier Transform (DFT) and also performs sharpening using the Unsharp sharpen approach. Then fusion is performed using Stationary Wavelet Transformation (SWT) technique to fused the enhanced images and obtaining more detail of the resultant image. The proposed approach is applied to two image sets, i.e., the "planes" and "clocks" image sets. The quality of the output image evaluated using both qualitative and quantitative approaches. Four will know quantitative metrics used to assess the performance of the novel technique. The experimental results of the novel methods showed efficient, improved outcomes and better for multi-focused image fusion. The SWT (LF+DFT) and SWT (Unsharp Mask) are 2.6 %, 1.8%, and 0.62%, 0.61% better than the best baseline measure, i.e., SWT, considering RMSE (Root Mean Square Error) for both image sets.