A fast and reliable fusion algorithm is the key to the practical application of image fusion technology, so the research of the fast fusion algorithm with a good fusion effect is particularly important. Based on the multi-resolution analysis, this paper discusses the principles of the PCNN fusion algorithm, wavelet transform and Laplace pyramid algorithm, and then performs image fusion experiments. Experimental results show that the fusion effect of the wavelet transform and PCNN algorithm is significantly higher than that of the Laplace pyramid algorithm.
In recent years, wavelet transform theory has been paid more and more attention in image fusion. With the development of wavelet transform image fusion, wavelet transform is introduced, and the basic principles and types of wavelet transform are introduced. Then, aiming at two images with different focal lengths, the discrete wavelet transform method of three-layer decomposition is used, the low-frequency and high-frequency components are fused by different fusion rules, and the differences of different fusion strategies in wavelet transform image fusion are compared and analyzed. Experimental results show that wavelet transform has the characteristics of convenient application, rapid fusion and real image, and has a good application prospect.
As an important branch in the field of image processing, image fusion has become one of the hot issues in research. For pixel-level image fusion, multi-scale multi-resolution decomposition has been widely used, but in the processing of lowfrequency sub-bands, because the averaging method is easy to lead to blurry fused images, contrast degradation and other issues, a low-frequency sub-band fusion method based on regional energy is proposed; For high-frequency subbands, the influence of their neighborhood coefficients is also considered while the coefficients themselves are considered. The fusion experiment of the registered image and the evaluation of the fusion image show that the method in this paper fully preserves the high-frequency edges and details of the image while preserving the image contour.
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