Image Fusion Using Wavelet Transformation and XGboost Algorithm  

作　　者：Shahid Naseem Tariq Mahmood Amjad Rehman Khan Umer Farooq Samra Nawazish Faten S.Alamri Tanzila Saba 

机构地区：[1]Department of Information Sciences,Division of S&T,University of Education,Lahore,54770,Pakistan [2]Artificial Intelligence and Data Analytics(AIDA)Lab,CCIS Prince Sultan University,Riyadh,11586,Saudi Arabia [3]Faculty of Information Sciences,University of Education,Vehari Campus,Vehari,61100,Pakistan [4]Department of Computer Science,University of Engineering and Technology,Taxila,47050,Pakistan [5]Department of Mathematical Sciences,College of Science,Princess Nourah Bint Abdulrahman University,Riyadh,84428,Saudi Arabia

出　　处：《Computers, Materials & Continua》2024年第4期801-817,共17页计算机、材料和连续体（英文）

基　　金：Princess Nourah bint Abdulrahman University and Researchers Supporting Project Number(PNURSP2024R346);Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia.

摘　　要：Recently,there have been several uses for digital image processing.Image fusion has become a prominent application in the domain of imaging processing.To create one final image that provesmore informative and helpful compared to the original input images,image fusion merges two or more initial images of the same item.Image fusion aims to produce,enhance,and transform significant elements of the source images into combined images for the sake of human visual perception.Image fusion is commonly employed for feature extraction in smart robots,clinical imaging,audiovisual camera integration,manufacturing process monitoring,electronic circuit design,advanced device diagnostics,and intelligent assembly line robots,with image quality varying depending on application.The research paper presents various methods for merging images in spatial and frequency domains,including a blend of stable and curvelet transformations,everageMax-Min,weighted principal component analysis(PCA),HIS(Hue,Intensity,Saturation),wavelet transform,discrete cosine transform(DCT),dual-tree Complex Wavelet Transform(CWT),and multiple wavelet transform.Image fusion methods integrate data from several source images of an identical target,thereby enhancing information in an extremely efficient manner.More precisely,in imaging techniques,the depth of field constraint precludes images from focusing on every object,leading to the exclusion of certain characteristics.To tackle thess challanges,a very efficient multi-focus wavelet decomposition and recompositionmethod is proposed.The use of these wavelet decomposition and recomposition techniques enables this method to make use of existing optimized wavelet code and filter choice.The simulated outcomes provide evidence that the suggested approach initially extracts particular characteristics from images in order to accurately reflect the level of clarity portrayed in the original images.This study enhances the performance of the eXtreme Gradient Boosting(XGBoost)algorithm in detecting brain malignancies with

关 键 词：Image fusion max-min average CWT XGBoost DCT inclusive innovations spatial and frequency domain 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]