Research On Medical X-Ray Image Enhancement Algorithm Based On Exposure Fusion

With the rapid development of computer and digital technology in medicine,a large number of new imaging technologies have been applied.Digital medical images provide an important medium for the transmission and medical information analysis.Nowadays,medical image processing plays a particularly important auxiliary role in medical diagnosis.Due to the complexity of the internal tissues and organs of the human body,exposure fusion can be affected by factors such as hardware equipment or X-ray scattering during the process of collecting medical images,which leads to issues such as unclear edge boundaries,uneven light distribution,and low contrast in medical X-ray images,which can affect the accuracy of doctors’ judgment of the condition.Therefore,medical X-ray image enhancement technology has irreplaceable significance in the medical field,The main work of this article is as follows:(1)In response to noise interference and poor image quality caused by low-dose CT in medical CT images,a method of improving medical CT images based on multidimensional exposure fusion has been proposed.Firstly,the input image is decomposed using a multiscale Laplace pyramid.Secondly,the image is reconstructed.During the reconstruction process,noise is filtered and details are extracted from the image.Finally,the exposure fusion algorithm is used to calculate the weight estimation matrix,exposure rate,and other related parameters.Compared with other commonly used enhancement algorithms,experiments show that the enhanced image detail edges of this algorithm are more convenient for human eyes to observe,and are more applicable and effective.(2)The medical CT enhancement method based on multiscale exposure fusion has achieved significant results in medical CT image enhancement,but there are still limitations in removing "halo" noise in medical X-ray images.Therefore,to address the problems of "halo artifact" noise,edge detail blur,and other issues in medical X-ray images,a method of improving medical X-ray images based on weighted fusion of the pointing filter exposure has been proposed.Firstly,a dark channel prior based defogging algorithm is used to remove noise such as "halo artifacts" in medical X-ray images.Secondly,use the Sobel operator-weighted loading filtering algorithm to improve the edge of the image.Finally,the contrast of the image is corrected using the exposure fusion algorithm.Compared to other common algorithms,experiments show that the algorithm in this paper greatly improves the clarity of the image without causing overexposure distortion,and the enhancement effect is more obvious.This article proposes two medical X-ray enhancement algorithms for two types of X-ray images,and a comparative analysis shows that the algorithm proposed in this article has advantages.