Image fusion is a very important data fusion, the branch is in the late 1970's, put forward the concept of synthesis is the sensor, image processing and signal processing, computer and modem technology of artificial intelligence.
Image fusion is to combine two or more sensors at the same time (or different time) for about a specific scene images or image sequence information comprehensive to generate a new interpretation of this scene.
Due to the large amount of images, the images to carry more kinds of understanding, and makes the image recognition, work hard to solve the image fusion technology is one of the important theories and methods. Image fusion comprehensive multiple sensors on the same things by the scan, the organic integration, complementary information to reduce or inhibit single source is perceived goals or environmental explain the meaning of the possible, incomplete, uncertainty and error, the maximum of image information to improve the utilization rate, thus greatly improve on feature extraction, classification and pattern recognition, etc.
This paper firstly introduces the classification of image fusion is introduced, and the traditional image fusion algorithm based on the classical multiresolution analysis algorithm, Then based on wavelet transform, and based on the first generation based on second-generation Curvelet Curvelet transform image fusion algorithm, this paper introduces the principle, and finally gives algorithm analysis and experiment results. Experimental results show that this method is simple, feasible to, and has a good effect and fast speed.
Data fusion is a very important branch of fusion is the late 70s of the 20th century the concept of the integrated sensors, image processing, signal processing, modern high-tech computers and artificial intelligence.
Image fusion is two or more sensors at the same time (or at different times) for a specific scene on the image or image sequence information to be integrated to produce a new interpretation of the this scenario.
As the amount of information carried by the image, image type and more, making image understanding, recognition and so difficult, image fusion is important to address this issue the theory and method. Image fusion combines multiple sensor scans of the same things photography, through the organic integration of complementary information, reduce or inhibit the single source of information on the perceived target or the environment may explain the existence of ambiguity, incompleteness, uncertainty and error , the maximum increase the utilization of a variety of image information, thereby greatly improving the feature extraction, classification and pattern recognition and so effective.
Introduction This paper introduces the classification of image fusion, image fusion algorithm and traditional multi-resolution analysis based on the classic algorithm; then based on wavelet transform, based on first-generation and second generation Curvelet transform Curvelet transform image fusion principle to do a detailed description of the algorithm are given experimental results and analysis. Experimental results show that the adopted method is simple and feasible, with good results and fast convergence speed.
Data fusion is a very important branch of fusion is the late 70s of the 20th century the concept of the integrated sensors, image processing, signal processing, modern high-tech computers and artificial intelligence.
Image fusion is two or more sensors at the same time (or at different times) for a particular scene on an image or image sequence information to be integrated to generate a new scenario to explain about this.
As the amount of information carried by the image, image type and more, making image understanding, recognition and so difficult, image fusion is important to address this issue the theory and method. Image fusion combines multiple sensor scans of the same things photography, through the organic integration of complementary information, reduce or inhibit the single source of information on the perceived target or the environment may explain the existence of ambiguity, incompleteness, uncertainty and error , the maximum increase the utilization of a variety of image information, thereby greatly improving the feature extraction, classification and pattern recognition and so effective.
Introduction This paper introduces the classification of image fusion, image fusion algorithm and traditional multi-resolution analysis based on the classic algorithm; then based on wavelet transform, based on first-generation and second generation Curvelet transform Curvelet transform image fusion principle to do a detailed description of the algorithm are given experimental results and analysis. Experimental results show that the adopted method is simple and feasible, with good results and fast convergence speed.
基于第一代Curvelet变换以及基于第二代Curvelet变换的图像融合算法原理做了详细的介绍,
基于第一代《曲波》变换以及基于第二代《曲波》变换的图像融合算法原理做了详细的介绍,
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Image fusion is a very important data fusion, the branch is in the late 1970's, put forward the concept of synthesis is the sensor, image processing and signal processing, computer and modem technology of artificial intelligence.
Image fusion is to combine two or more sensors at the same time (or different time) for about a specific scene images or image sequence information comprehensive to generate a new interpretation of this scene.
Due to the large amount of images, the images to carry more kinds of understanding, and makes the image recognition, work hard to solve the image fusion technology is one of the important theories and methods. Image fusion comprehensive multiple sensors on the same things by the scan, the organic integration, complementary information to reduce or inhibit single source is perceived goals or environmental explain the meaning of the possible, incomplete, uncertainty and error, the maximum of image information to improve the utilization rate, thus greatly improve on feature extraction, classification and pattern recognition, etc.
This paper firstly introduces the classification of image fusion is introduced, and the traditional image fusion algorithm based on the classical multiresolution analysis algorithm, Then based on wavelet transform, and based on the first generation based on second-generation Curvelet Curvelet transform image fusion algorithm, this paper introduces the principle, and finally gives algorithm analysis and experiment results. Experimental results show that this method is simple, feasible to, and has a good effect and fast speed.