Research On Pixel-level Image Fusion Algorithm Based On Water Wave Optimization And Contourlet Transform

The image is an important source for people to obtain information.Research on digital image processing has always been a hot topic.Image Fusion(Image Fusion)is a two-dimensional image processing technology that combines and synthesizes preprocessed and registered images.Through the effective use of redundant information and complementary information of different images,the image fusion and imaging are finally obtained.A more complete and accurate image description of the object.Image fusion is divided into spatial domain fusion and transform domain fusion.Spatial domain fusion related algorithm fusion speed is fast,but the fusion effect is general.The fusion algorithm of transform domain fusion related algorithm is complex,but the calculation is large but the fusion effect is excellent.Contourlet transform is a research hotspot in the field of image signal processing at home and abroad.It has all the advantages of wavelet transform and can efficiently approximate and describe the inherent geometric structure of the image such as outline,edge and texture.It has important theoretical significance and practical application Value.In addition,the image fusion process involves a large number of operations and can be solved by an optimization algorithm.Water wave optimization algorithm is a recently proposed heuristic optimization algorithm with good optimization performance.This paper focuses on the study of pixel-level image fusion methods based on water wave optimization algorithm and Contourlet transform.The main contents are as follows:1.Two registered images can be used for image fusion operation.The traditional registration method needs to traverse all the pixels of the image to find the optimal matching position,which requires a large amount of calculation and takes a long time.This paper presents a fast image matching algorithm based on water wave optimization and grey correlation analysis,which uses the grey correlation degree to measure the similarity of two images and set it as the objective function.Then the water wave optimization algorithm quickly approaches the optimal matching point.Experiments have shown that this method has good matching accuracy,greatly reduces calculation time,and has good matching results for noise images.2.Spatial domain fusion algorithm fusion speed is fast,but the fusion effect is general.This paper proposes a spatial domain-based image fusion method based on the mean reference,can effectively improve the contrast of the fusion image: The pixel value of a certain point of the fused image is determined as the pixel value of the point in each source image that is the largest from its average gray value.This operation is performed on all the pixels of the fused image to obtain the fusion result image.Experiments show that this method is especially suitable for multi-focus image fusion,and the sharpness and contrast of the fused image are significantly improved compared with the commonly used algorithms.3.The Contourlet transform is deeply studied.This paper proposes an optimized Contourlet transform image fusion method based on Water Wave Optimization,which decomposes the single weight of the traditional Contourlet transform into multi-scale and multi-direction weighted sets,and automatically solves this weighted set using the water wave optimization algorithm.Experiments show that the fusion effect of the proposed method is significantly improved compared with the original Contourlet transform fusion method.