Multi-resolution transmission image registration based on “Terrace Compression Method” and normalized mutual information

Abstract

Multispectral transmission images provide the possibility for the early diagnosis of breast cancer, and promote the study of family self-screening of breast tumors. However, the scattering characteristic of biological tissue leads to transmission images with fuzzy boundaries and poor contrast. And there are different offsets in the captured image sequences because of the instability of the human body such as breathing and slight jitter, which will affect the data precision. In view of the above problems, a multi-resolution image registration method combining “Terrace Compression Method” and normalized mutual information (NMI) is proposed, and the effectiveness of the method is verified by taking the transmission image of wavelength at 435 ​nm as an example. First of all, the gray-scale values of the selected boundary region of heterogeneity are sorted. According to the “Terrace Gradient” of gray-scale values, multiple gray-scale intervals are divided to enhance the gradient information of the image. Then, the image of the terraced shape of each gray-scale interval is extracted respectively, and the edge detection result is obtained by the Sobel operator. Finally, the Gaussian pyramid model is used for image down-sampling to achieve multi-resolution image registration by combining with NMI similarity measure. Compared with the other registration methods, the method proposed in this paper can detect the transformation relationship between images more accurately and effectively, and the similarity of the registered image with the reference image is also higher. The combination of the “Terrace Compression Method” and NMI effectively improves the registration accuracy of transmission images, and provides favorable conditions for achieving heterogeneity detection in multispectral transmission images.