Photon Counting Image Fusion Algorithm Based on Adaptive Threshold of Regional Energy

Abstract

In order to get photon counting fusion images with better effect, it is proposed a fusion algorithm based on adaptive threshold of regional energy fusion rule. The photon counting image is obtained by the MPPC (Multi-pixel Photon Counter) single detector in different illumination conditions, the high-frequency part and the low-frequency part are obtained after redundant wavelet transform of photon counting image. In high-frequency part of the two source images, the energy of the corresponding region, neighborhood mean square, matching degree and adaptive threshold deviation are calculated. And the adaptive threshold is determined by pixel values and mean values of regional image. If the matching degree is greater than adaptive threshold value, weighted regional energy fusion method is used to solve it. Otherwise, the enhanced pixel value of source image with larger energy in local region is selected as pixel value in corresponding fusion image. Using adaptive threshold of regional energy fusion rule for image fusion, it is proved that details of photon counting fusion image are clearer and target is easier to recognize in this paper, the values of information entropy, average gradient and spatial frequency are about 20%, 25%, and 30% higher than that of regional energy fusion rules.