Research On Fusion Algorithms Of Infrared And Visible Images

With the development of image fusion technology, the applications of infraredsensors and visible light sensors become more widespread. Meanwhile, a higherrequirement for fusion algorithms about infrared images and visible images isproposed. Currently, the size of the image obtained from the sensor increases. Withregard to the fusion algorithms for pixel operations, this change takes a lot ofchallenges on the storage and computing. Compressed sensing theory provides a newway to solve this problem. When the sensor is obtaining images, external factorsmay disturber the process. And these factors reduce the image’s contrast. Thus,higher requirements for the fusion algorithm are put forward. Not only can the fusionalgorithm blend the complementary information, but also remove the redundantinformation. At the same time, it is better for the algorithm to improve the visualeffect of the fusion image. The fusion image plays a very important role for thealgorithm evaluation. It can not only make fusion algorithm improved and perfected,but also evaluate the property of the algorithm.The paper has carried lots of studies on these three aspects. There are severalresearch results as follows.1. Through the analysis and research of multi-scale compression perceptiontheory, we proposed a new fusion algorithm on infrared images and visible images.This algorithm is based on the discrete undersampling theory. By combiningcontourlet transform algorithm and wavelet transform algorithm, We can get the image with more sparse expression. According to the characteristics of thecoefficient of energy distribution after transformation, a new discrete doubleradiation sampling mode is proposed. According to the characteristics of thecoefficient of each layer after sampling, the appropriate rules of fusion are used. Thismethod improves the quality of the fused image.2. In the process of image capture, the image contrast may be variation; theimage visual effect may be descended. To solve these problems, a new algorithm isproposed. This algorithm can improve the contrast of the fused image. By using thebilateral filtering, this method works out the halo phenomena appeared in the processof image enhancement of Retinex method with multiscale subband decomposition.This method is applied to image fusion. It not only enhances the image contrast, butalso increases the detail of the image.3. In view of the traditional fusion image, there is a problem for the imagequality. Evaluation results of objective evaluation indicators are different fromsubjective visual perception. In order to solve this problem, a new evaluation indexof fusion image quality is proposed. The index is a kind of objective evaluationcriteria that conforms to the human eye visual features. In the calculation of thevisual information fidelity, contrast sensitivity is introduced as a weight of thesummation. It solves a problem of high value. The value is brought by the visualinformation fidelity when it is evaluating a enhance image. The experimental resultsshow that, the evaluation result is consistent with the subjective evaluation results.And, the algorithm is simple. Therefore, it has a certain practical value.