Because previous methods can not identify underlying image features from noises effectively, the updated image fusion schemes will be degraded when inputs are corrupted with noise. The perceptual salient image feature...Because previous methods can not identify underlying image features from noises effectively, the updated image fusion schemes will be degraded when inputs are corrupted with noise. The perceptual salient image features often manifest some geometric structures, while noise dominated images are less structured. Based on complex wavelet transform, a structurization information metric is formulated by means of the Von Neumann entropy. The formulated metric can distinguish image features from noise very well. During the fusion process, the metric is employed to weight all fusion inputs. As a result, the perceptual meaningful inputs are enhanced while the noise inputs are de-emphasized adaptively. Comparing several image fusion schemes subjectively and objectively shows the good performance of the new scheme.展开更多
文摘Because previous methods can not identify underlying image features from noises effectively, the updated image fusion schemes will be degraded when inputs are corrupted with noise. The perceptual salient image features often manifest some geometric structures, while noise dominated images are less structured. Based on complex wavelet transform, a structurization information metric is formulated by means of the Von Neumann entropy. The formulated metric can distinguish image features from noise very well. During the fusion process, the metric is employed to weight all fusion inputs. As a result, the perceptual meaningful inputs are enhanced while the noise inputs are de-emphasized adaptively. Comparing several image fusion schemes subjectively and objectively shows the good performance of the new scheme.
