Microscopic image fusing method based on two-dimensional empirical mode decomposition

Abstract

The invention relates to a microscopic image fusing method based on two-dimensional empirical mode decomposition, which comprises the following steps: performing multi-scale decomposition on the acquired ordered microscopic original images by using a two-dimensional empirical mode decomposition method, thereby acquiring the multi-scale high-frequency components of original images; fusing the multi-scale high-frequency components according to local obvious standard; fusing the low-frequency components of the original images by using a principal component analysis method; and finally reversely recomposing to acquire a merged image. By using the method provided by the invention, the multi-scale decomposition is performed on the acquired ordered microscopic original images by using the two-dimensional empirical mode decomposition method and the decomposition process is adaptive; high-frequency fusing treatment is performed according to the local obvious standard based on a big area value and the relevance between adjacent coefficients is considered, so the detail information clearly focused of each original image can be supplied; and the low-frequency fusing treatment is performed by using the principal component analysis method, so the relevant information of original image pixel is utilized and the visual decoding effect of the merged image is increased, thereby increasing the quality of the fused image.

Description

technical field [0001] The present invention relates to image fusion technology, in particular to a microscopic image fusion method based on two-dimensional empirical mode decomposition, which is used to fuse multiple images with different focus positions in the microscopic imaging process, and is obtained by extracting local clear sequence images The entire clear image is especially suitable for microscopic imaging under the condition of infrared light source. Background technique [0002] Image fusion is an information fusion technology whose main research content is image. It is to combine two or more images into one image to obtain a more accurate, comprehensive and reliable image description of the same scene. Image fusion technology effectively utilizes the redundancy and complementarity between multiple images to make the fused image more suitable for human visual perception, suitable for the needs of computer understanding, analysis and subsequent processing, such as...

AI Technical Summary

Problems solved by technology

[0004] Various spatial fusion methods have fast calculation speed, but when dealing with microscopic images with a large degree of defocus, they are prone to block effects and the effect is not ideal

[0005] The multi-resolution analysis method represented by wavelet transform has good smoothing performance and has been widely used and recognized at present, but this method has two problems: one is that the extracted features can only reflect the translation and expansion of the image in a single function. The energy on the function formed; the second is to select the wavelet basis and some parameters

[0008] To sum up, when the current existing fusion technology is applied to the fusion of sequential microscopic images, especially the fusion of microscopic images under the condition of infrared light source, there are still some deficiencies: various spatial fusion methods have block effect problems; wavelet transform methods only Extracting detailed information in the three directions of horizontal, vertical and diagonal requires selection of parameters such as wavelet base, and the quality of parameter selection has a great impact on the fusion result

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