Research On Medical Image Enhancement Algorithm Based On Improved Total Variational And Guided Filtering

Medical imaging technology is a method of examining the interior of the human body using various devices,with various imaging modes such as X-ray,CT,MRI,ultrasound,etc.During image acquisition,it may be affected by factors such as noise,scattering,and lighting,resulting in poor image quality.So,it is necessary to enhance medical images,improve their contrast and clarity,and enhance detailed information.In this way,doctors can diagnose and treat the condition more accurately.Medical image enhancement technology is of great significance in the medical field.Aiming at the importance of medical image enhancement technology,this study explored the application of several commonly used image enhancement algorithms in the field of medical image,and summarized their enhancement effects and existing problems.Based on this,this paper proposes an improved medical image enhancement algorithm and uses multiple data sets to verify it.The main research contents include:(1)The application of several commonly used image enhancement algorithms,such as histogram equalization,CLAHE enhancement algorithm and Retinex algorithm,in medical image enhancement is studied and analyzed,and their applicability and effect in medical image enhancement are evaluated by comparing the performance and effect of different algorithms.(2)In order to solve the problems of noise,detail,halo and over-enhancement in traditional medical image enhancement algorithms,a new medical image enhancement algorithm is proposed.The algorithm uses the improved Retinex and multi-image fusion algorithm to split the image to be processed into three parts and adopt different processing methods.Among them,the first uses improved histogram equalization and bilateral filtering,the second uses improved Retinex algorithm,and the third uses image enhancement based on Butterworth low-pass filtering and histogram equalization.Finally,the enhanced image is obtained by multi-image fusion technology.Experimental results show that the algorithm can effectively improve the quality of low-quality medical images,reduce image noise and maintain edge information.In addition,the algorithm is evaluated using objective evaluation indicators to verify its effectiveness.(3)In the field of medical image processing,the full variation model algorithm is widely used,but in the process of processing,it is easy to appear "ladder effect",that is,discontinuous block structure,resulting in reduced visual quality and detail effect.To this end,a new medical image enhancement algorithm is proposed,which uses the total variation of edge adaptive direction to construct the filtered image of guided filtering,and provides better geometric structure information to assist the guided filtering algorithm in image enhancement.Compared with the traditional total variation model,this algorithm can better eliminate the ladder effect and noise,and has better enhancement effect.Experimental results show that the algorithm has significant advantages in the field of medical image enhancement.In addition,the algorithm has wide application prospects and practicability.