Contrast Correction Using Hybrid Statistical Enhancement on Weld Defect Images

作     者：Wan Azani Mustafa Haniza Yazid Ahmed Alkhayyat Mohd Aminudin Jamlos Hasliza ARahim Midhat Nabil Salimi 

作者机构：Advanced Computing(AdvCOMP)Centre of ExcellenceUniversiti Malaysia Perlis(UniMAP)Pauh Putra CampusArau02600PerlisMalaysia Faculty of Electrical Engineering TechnologyUniversiti Malaysia Perlis(UniMAP)Pauh Putra CampusArau02600PerlisMalaysia Faculty of Electronic Engineering TechnologyUniversiti Malaysia Perlis(UniMAP)Pauh Putra CampusArau02600PerlisMalaysia Faculty of Engineeringthe Islamic University54001NajafIraq Faculty of Chemical Engineering TechnologyUniversiti Malaysia Perlis(UniMAP)Arau02600PerlisMalaysia 

出 版 物：《Computers, Materials & Continua》 (计算机、材料和连续体（英文）)

年 卷 期：2022年第71卷第6期

页      面：5327-5342页

核心收录：

学科分类：08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

主　　题：Contrast enhancement image statistic weld defect 

摘      要：Luminosity and contrast variation problems are among the most challenging tasks in the image processing field,significantly improving image *** is implemented by adjusting the dark or bright intensity to improve the quality of the images and increase the segmentation ***,numerous methods had been proposed to normalise the luminosity and contrast variation.A new approach based on a direct technique using statistical data known as Hybrid Statistical Enhancement(HSE)is presented in this *** method uses themean and standard deviation of a local and global neighbourhood and classified the pixel into three groups;the foreground,border,and problematic region(contrast&luminosity).The datasets,namely weld defect images,were utilised to demonstrate the effectiveness of the HSE *** results from the visual and objective aspects showed that the HSE method could normalise the luminosity and enhance the contrast variation problem *** proposed method was compared to the two(2)populor enhancement methods which is Homomorphic Filter(HF)and Difference of Gaussian(DoG).To prove the HSE effectiveness,a few image quality assessments were presented,and the results were *** HSE method achieved a better result compared to the other methods,which are Signal Noise Ratio(8.920),Standard Deviation(18.588)and Absolute Mean Brightness Error(9.356).In conclusion,implementing the HSE method has produced an effective and efficient result for background correction and quality images improvement.