Research On Motion Detection And Deghosting In Multi-exposure Fusion

With the continuous development of digital camera technology,digital images are increasingly appearing in people's production,life and scientific research.In recent years,high dynamic range imaging technology research and progress,greatly promoted the digital imaging technology towards high-definition and high information development direction.At the same time,this technology has also been increasingly applied to digital camera,telemetry remote sensing,security monitoring and other fields.Based on the technical principles of digital imaging,high dynamic range imaging,multi-exposure image fusion and ghosting elimination,this paper summarizes the existing multi-exposure image fusion algorithms and classifies them based on the operation domain and the reference image pair algorithm And comparison.On this basis,two new motion detection and ghost elimination algorithms in multi-exposure image fusion are proposed.The main contents and main work of this paper are as follows:1.In-depth study of high dynamic range imaging technology,especially multi-exposure image fusion technology.This paper expounds the theoretical basis of motion detection and ghost removal technology in dynamic scene,the current research situation and the current technical difficulties in the world,and classifies the existing motion detection and ghost removal algorithms.2.An efficient "ghosting" detection and removal algorithm based on intra-consistency and inter-consistency is proposed for the first time to realize the non-ghost reconstruction of high dynamic range(HDR)image.The algorithm is detected by substituting the histogram map matching operation for the selected reference image and the other images in the image sequence,instead of the motion data movement operation.This method can make most of the details of the scene to be retained,especially in the image of the exposed or overexposed area,and greatly reduces the difficulty of late motion detection.In addition,the motion detection model is established at the super pixel level,taking into account the internal consistency between the pixels at the same position of different images and the external consistency between adjacent pixels in the same image.This method effectively calibrates the input low dynamic range image sequence and preserves the details of the image to the maximum extent under the condition of removing the ghost.3.A motion detection and ghost removal algorithm based on structural consistency and contrast quality is proposed for the first time.The motion area is detected by comparing the structural consistency between the other image and the reference image.In order to keep the details of the scene more,the contrast index is introduced to evaluate the visibility,and under the guidance of the contrast map,the intermediate image sequence is seamlessly merged to produce an image without ghosts.The details in some of the scenes are preserved.In addition,this method greatly reduces the computational complexity of traditional algorithms.