CONTRAST ENHANCEMENT FOR MULTI-MODALITY IMAGE FUSION IN SPATIAL DOMAIN

摘要

In some scenes that cover a large area, some of the cameras capture images that may be affected by weather conditions or illumination changes, this causes the exposure of these images to a lack of focus, blur, or/and noise. Multi-model image fusion is a significant technique in computer vision and image processing to solve these problems. In this paper, a multi-model image fusion is proposed and presented in three case studies. Each case has a different scheme and all cases have the same goal. The goal of the proposed algorithm is to enhance the source images in spatial domain before fusion process leading to increase the quality of fused image. The techniques, which are used in the proposed method, are Principle Component Analysis, Histogram Equalization; sharpen filter, and Weighted Averaging fusion. Comparison analysis is achieved using some focus measurements to test the performance of the proposed algorithm in the three cases comparing with the baseline fusion techniques. The experimental results showed that the proposed method obtains better performance in preserving gradation contrast and enhancing fused image quality.