An evaluation method of image fusion based on region similarity

作者：Luo Xiao Qing^*; Wu Xiao Jun

来源：Acta Electronica Sinica, 2010, 38(5): 1152-1155.

• Dimensionality reduction
• Evaluation Method
• Fused images
• Fusion evaluation
• Fuzzy c-means clustering algorithms
• Human perception
• Image regions
• Image variations
• Local region
• Principal eigen-vector
• Region similarity
• Regional feature

A quantitative metric was proposed to objectively evaluate the quality of fused images. First, the Fuzzy C-Means clustering algorithm (FCM) was used to segment image in order to obtain the regional feature matrix. After dimensionality reduction, we could calculate the distance between regions as regional similarity. Secondly, we used the ratio of the principal eigenvector derived from two original corresponding image regions as the weight of corresponding regions. The ratio of edge vectors amplitude between regions was used to denote local region saliency. Finally, we could attain the similarity between images. The results show that the proposed metric is more consistent with the human perception nature as it considers the local image variations and the regional saliency.

• 出版日期2010
• 单位江南大学