暨南大学学报(自然科学与医学版)
暨南大學學報(自然科學與醫學版)
기남대학학보(자연과학여의학판)
JOURNAL OF JINAN UNIVERSITY(NATURAL SCIENCE & MEDICINE EDITION)
2015年
3期
191-201
,共11页
赵雨%林晓佳%阳维%冯前进
趙雨%林曉佳%暘維%馮前進
조우%림효가%양유%풍전진
DR 图像%图像增强%加权红 -黑小波(WRB)
DR 圖像%圖像增彊%加權紅 -黑小波(WRB)
DR 도상%도상증강%가권홍 -흑소파(WRB)
digital radiography (DR)image%image enhancement%weighted red-black wavelets (WRB)
目的:数字化 X 线图像(DR)细节常被淹没、动态范围宽.本研究使用了一种基于加权红-黑小波(WRB)变换的增强方法解决这一问题.方法:原始 DR 图像先进行对数变换,然后对变换后的图像进行 WRB 分解得到各层的系数;通过设计的分段非线性子带系数操作函数,分别对各层系数进行处理,最后利用 WRB 反变换和处理过的子带系数重构出增强的图像.结果:WRB 方法测试原始 DR 图像,平均运行时间约为0.6 s;利用该方法对DR 图像进行增强后,图像细节显示效果和对比度均得到提升,且无光晕伪影产生;与一些常用的增强算法相比,用WRB 算法增强的图像信息熵和交叉熵指标均较优.结论:相比一些传统增强算法,基于加权红-黑小波变换的 DR图像增强方法具有明显优势,不仅能有效压缩图像动态范围,还增强图像细节和对比度.
目的:數字化 X 線圖像(DR)細節常被淹沒、動態範圍寬.本研究使用瞭一種基于加權紅-黑小波(WRB)變換的增彊方法解決這一問題.方法:原始 DR 圖像先進行對數變換,然後對變換後的圖像進行 WRB 分解得到各層的繫數;通過設計的分段非線性子帶繫數操作函數,分彆對各層繫數進行處理,最後利用 WRB 反變換和處理過的子帶繫數重構齣增彊的圖像.結果:WRB 方法測試原始 DR 圖像,平均運行時間約為0.6 s;利用該方法對DR 圖像進行增彊後,圖像細節顯示效果和對比度均得到提升,且無光暈偽影產生;與一些常用的增彊算法相比,用WRB 算法增彊的圖像信息熵和交扠熵指標均較優.結論:相比一些傳統增彊算法,基于加權紅-黑小波變換的 DR圖像增彊方法具有明顯優勢,不僅能有效壓縮圖像動態範圍,還增彊圖像細節和對比度.
목적:수자화 X 선도상(DR)세절상피엄몰、동태범위관.본연구사용료일충기우가권홍-흑소파(WRB)변환적증강방법해결저일문제.방법:원시 DR 도상선진행대수변환,연후대변환후적도상진행 WRB 분해득도각층적계수;통과설계적분단비선성자대계수조작함수,분별대각층계수진행처리,최후이용 WRB 반변환화처리과적자대계수중구출증강적도상.결과:WRB 방법측시원시 DR 도상,평균운행시간약위0.6 s;이용해방법대DR 도상진행증강후,도상세절현시효과화대비도균득도제승,차무광훈위영산생;여일사상용적증강산법상비,용WRB 산법증강적도상신식적화교차적지표균교우.결론:상비일사전통증강산법,기우가권홍-흑소파변환적 DR도상증강방법구유명현우세,불부능유효압축도상동태범위,환증강도상세절화대비도.
Aim:An enhancement algorithm based on weighted red-black wavelets (WRB)transform is presented to solve the problems of details buried and wide dynamic range in original DR images.Meth-ods:logarithmic transformation was first performed on the original DR images.then,the changed images were decomposed within the WRB architecture to get the wavelet coefficients of each layer.Furthermore a piecewise nonlinear coefficient operation function was designed to process the coefficients.In the end, the enhanced images were reconstructed by the inverse WRB transform.Results:The proposed algorithm is tested on the original DR images and compared with some other enhancement algorithms.The average running time of our algorithm is about 0.6 seconds and significantly faster than the other algorithms.U-sing our enhancement algorithm,both of the details and local contrast of the DR images are promoted, meanwhile no halo artifacts have been produced in the enhanced images.Furthermore,the information entropy and cross entropy indices of our algorithm are better than that of the other algorithms.Conclu- <br> sion:The proposed enhancement algorithm is an effective and efficient method for compressing image dy-namic range,enhancing image details of the original DR images.