Image Fusion Algorithm Based On Quantum Theory

In recent years, with the rapid development of high precision sensor technology and digital image processing technology, the development and application of digital image fusion technology is become more and more a hot issue in the field of image processing research. Digital image fusion fuse two or more images which about the same scene images got by two sensors, or images got by the same sensor in different time.After image processing and computer technology, the fused image can get the maximum useful information of source image, and finally integrated into an high quality and have the application value image. Image fusion technology can effectively reduce the develop tasks of hardware, eliminate error and uncertainty in the process of extracting the source image which come from the different environment and machines.The image fusion can largely take advantage of the effective information of source image, it is better for the further image processing, such as image enhancement, the compression and feature extraction, recovery and noise denoising, target track and three-dimensional reconstruction.Quantum information science is a new born subject whichcombined with physical science and classical information science, it took much advantage of properties of quantum mechanics to express the new concept,method and theory, and brings many new development of sight. The quantum derivative images fusion algorithm is concrete application in digital image processing methods.Firstly, the paper briefly introduced the origin and development of quantum information processing as well as the related concepts of the digital image fusion, and the source of this project. Then introduced and reasoned the basic conception, theory and mathematical formula from both physic basis of quantum mechanics and mathematics foundation of quantum information in detail,including quantum bit, quantum superposition principle, quantum measurement collapse, vector,inner product and cross product, tensor product and so on. The third chapter mainly introduce the currently used image fusion algorithm, including simple fusion algorithm、Laplacian pyramid fusion algorithm and wavelet fusion algorithm. The focus of the article is in chapter four, make use of the pseudo quantum bit correlation form of image and corresponding collapse model to set up a small field image gray correlation systems and do its multi-level analysis. From this we can getpyramid decomposition model based on quantum theory, then chose the average gradient solution and the adaptive weighted fusion rules based on the quantum theory according to the graphic characteristics of each pyramid decomposition layers. The simulation experiments show that the fused image by inversion algorithm has its unique superiority than traditional Laplacian pyramid algorithm and wavelet fusion algorithm in the details, edge features and image clarity.