测绘学报
測繪學報
측회학보
ACTA GEODAETICA ET CARTOGRAPHICA SINICA
2015年
8期
884-892
,共9页
遥感图像%图像增强%非下采样 Shearlet 变换(NSST)%参数化对数图像处理(PLIP)模型%模糊增强
遙感圖像%圖像增彊%非下採樣 Shearlet 變換(NSST)%參數化對數圖像處理(PLIP)模型%模糊增彊
요감도상%도상증강%비하채양 Shearlet 변환(NSST)%삼수화대수도상처리(PLIP)모형%모호증강
remote sensing image%image enhancement%non-subsampled Shearlet transform (NSST)%parameters logarithmic image processing (PLIP)model%fuzzy enhancement
针对部分遥感图像整体亮度偏暗、对比度较低的特点,为提高遥感图像的视觉效果和可解译性,提出了一种基于非下采样 Shearlet 变换(non-subsampled shearlet transform,NSST)和参数化对数图像处理(parameterized logarithmic image processing,PLIP)模型的遥感图像增强方法。首先,遥感图像经非下采样 Shearlet 变换分解成低频分量和高频分量；然后依据 PLIP 模型对其低频分量进行增强,提高图像的对比度；同时利用改进的模糊增强方法对高频分量进行增强,突显边缘细节信息。大量试验结果表明,与双向直方图均衡增强、基于平稳小波变换的增强、基于非下采样 Contourlet 变换的增强等5种图像增强方法相比,本文提出的方法在主观视觉效果和对比度、清晰度等客观定量评价指标两个方面均有优势,能更有效地提高遥感图像的对比度、增强边缘纹理细节信息,视觉效果更佳。
針對部分遙感圖像整體亮度偏暗、對比度較低的特點,為提高遙感圖像的視覺效果和可解譯性,提齣瞭一種基于非下採樣 Shearlet 變換(non-subsampled shearlet transform,NSST)和參數化對數圖像處理(parameterized logarithmic image processing,PLIP)模型的遙感圖像增彊方法。首先,遙感圖像經非下採樣 Shearlet 變換分解成低頻分量和高頻分量；然後依據 PLIP 模型對其低頻分量進行增彊,提高圖像的對比度；同時利用改進的模糊增彊方法對高頻分量進行增彊,突顯邊緣細節信息。大量試驗結果錶明,與雙嚮直方圖均衡增彊、基于平穩小波變換的增彊、基于非下採樣 Contourlet 變換的增彊等5種圖像增彊方法相比,本文提齣的方法在主觀視覺效果和對比度、清晰度等客觀定量評價指標兩箇方麵均有優勢,能更有效地提高遙感圖像的對比度、增彊邊緣紋理細節信息,視覺效果更佳。
침대부분요감도상정체량도편암、대비도교저적특점,위제고요감도상적시각효과화가해역성,제출료일충기우비하채양 Shearlet 변환(non-subsampled shearlet transform,NSST)화삼수화대수도상처리(parameterized logarithmic image processing,PLIP)모형적요감도상증강방법。수선,요감도상경비하채양 Shearlet 변환분해성저빈분량화고빈분량；연후의거 PLIP 모형대기저빈분량진행증강,제고도상적대비도；동시이용개진적모호증강방법대고빈분량진행증강,돌현변연세절신식。대량시험결과표명,여쌍향직방도균형증강、기우평은소파변환적증강、기우비하채양 Contourlet 변환적증강등5충도상증강방법상비,본문제출적방법재주관시각효과화대비도、청석도등객관정량평개지표량개방면균유우세,능경유효지제고요감도상적대비도、증강변연문리세절신식,시각효과경가。
Aiming at parts of remote sensing images with dark brightness and low contrast,a remote sensing image enhancement method based on non-subsampled Shearlet transform and parameterized logarithmic image processing model is proposed in this paper to improve the visual effects and interpret-ability of remote sensing images.Firstly,a remote sensing image is decomposed into a low-frequency component and high frequency components by non-subsampled Shearlet transform.Then the low frequency component is enhanced according to PLIP (parameterized logarithmic image processing)model,which can improve the contrast of image,whi le the improved fuzzy enhancement method is used to enhance the high frequency components in order to highlight the information of edges and details.A large number of experimental results show that,compared with five kinds of image enhancement methods such as bidirectional histogram equalization method,the method based on stationary wavelet transform and the method based on non-subsampled contourlet transform,the proposed method has advantages in both subjective visual effects and objective quantitative evaluation indexes such as contrast and definition, which can more effectively improve the contrast of remote sensing image and enhance edges and texture details with better visual effects.
