计算机工程与应用
計算機工程與應用
계산궤공정여응용
COMPUTER ENGINEERING AND APPLICATIONS
2015年
9期
191-195,226
,共6页
X射线图像%多尺度Retinex%高斯卷积%均值模板%图像灰度级映射
X射線圖像%多呎度Retinex%高斯捲積%均值模闆%圖像灰度級映射
X사선도상%다척도Retinex%고사권적%균치모판%도상회도급영사
X ray image%Multi-Scale Retinex(MSR)%Gaussian convolution%mean template%map the image gray-level
医学X射线图像通常存在亮度低,对比度差,造成难以识别的问题。为了增强此类图像,在Land提出的单尺度Retinex理论之上,论述基于此原理的多尺度Retinex(MSR)图像增强方法。利用均值模板代替高斯卷积模板对图像进行滤波,并且改进了将图像映射到设备显示器上的canonical gain/offset修正方法。实验将改进的修正方法用于多尺度的Retinex之上并与直方图均衡化和伽马校正方法进行对比。实验结果表明图像亮度的增强和对比度提高优于上述其他两种方法,新提出的方法较原有方法有效地提高了图像的信息熵,满足医学图像的诊断需求。
醫學X射線圖像通常存在亮度低,對比度差,造成難以識彆的問題。為瞭增彊此類圖像,在Land提齣的單呎度Retinex理論之上,論述基于此原理的多呎度Retinex(MSR)圖像增彊方法。利用均值模闆代替高斯捲積模闆對圖像進行濾波,併且改進瞭將圖像映射到設備顯示器上的canonical gain/offset脩正方法。實驗將改進的脩正方法用于多呎度的Retinex之上併與直方圖均衡化和伽馬校正方法進行對比。實驗結果錶明圖像亮度的增彊和對比度提高優于上述其他兩種方法,新提齣的方法較原有方法有效地提高瞭圖像的信息熵,滿足醫學圖像的診斷需求。
의학X사선도상통상존재량도저,대비도차,조성난이식별적문제。위료증강차류도상,재Land제출적단척도Retinex이론지상,논술기우차원리적다척도Retinex(MSR)도상증강방법。이용균치모판대체고사권적모판대도상진행려파,병차개진료장도상영사도설비현시기상적canonical gain/offset수정방법。실험장개진적수정방법용우다척도적Retinex지상병여직방도균형화화가마교정방법진행대비。실험결과표명도상량도적증강화대비도제고우우상술기타량충방법,신제출적방법교원유방법유효지제고료도상적신식적,만족의학도상적진단수구。
Medical X ray images are usually difficult to identify because of the poor brightness and low contrast. In order to enhance these images, this paper discusses the Multi-Scale Retinex(MSR)image enhancement method on the basis of the Single-Scale Retinex put forward by Land. A fact is emphasized that the calculation in image filtering can use a mean template as an alternative to Gaussian convolution template, and an improved method of canonical gain/offset is proposed to map the image gray-level on display devices in this paper. Further experiments compare the new method based on Multi-Scale Retinex with histogram equalization and gamma correction. It can be seen from the experimental results that the proposed method enhances image brightness and contrast ratio compared to the other two mentioned methods, and the entropy of X ray images is improved by the new introduced method; therefore the algorithm can satisfy the demand of medical image diagnosis.