IEEE Access (Jan 2019)
A Fusion Method in Frequency Domain for Multi-Wavelength Transmission Image
Abstract
Multi-wavelength transmission imaging provides a possibility for early breast cancer detection. However, due to the strong scattering effect of light source in the transmission process of biological tissue, there exist many difficulties in the heterogeneous identification of multi-wavelength images. In this paper, a multi-wavelength images frequency fusion method based on regional variance significance and regional space energy weighting is proposed to improve the accuracy of heterogeneous detection. Firstly, the acquisition experiment of phantom multi-wavelength transmission images is designed. And R\G\B three-channel wavelength images are extracted from multi-wavelength images as an example to realize subsequent image fusion. Secondly, frame accumulation technique and second-order Butterworth filter are used to improve the signal-to-noise ratio of images and suppress the noise of images. Then, after homomorphic filtering, it is found that the same frequency domain of images is connected, which is not conducive to the recognition of heterogeneity in image. In order to break the connectivity of images in the same frequency domain and improve the accuracy of heterogeneous detection, the regional variance significance and the regional space energy weighting fusion strategies are used to reconstruct the low-frequency and high-frequency fusion images respectively. Finally, the heterogeneous detection results of the proposed image fusion method and the state-of-the-art methods in the multi-wavelength image are compared. The experimental results show that compared with the state-of-the-art image fusion methods, the fusion method proposed in this paper can identify the location of heterogeneous region more accurately and significantly improve the contrast between heterogeneous region and normal region in the fusion image. In conclusion, the fusion algorithm not only effectively realizes the recognition of heterogeneity in multi-wavelength images, but also promotes the potential application of multi-wavelength transmission image in early breast cancer detection.
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