医学影像物理学03 数字图像I

DigitalImageFundmentWhatisImage?ImageImageofobjectMathematicFunctionPicturePhoticImageContinueFunctionDiscreteFunctionInvisibleImage图像与影像2DigitalImage?Sincecomputersstoredataandunderstanddatainanumericalform,wecansaythatanimageisanumericalrepresentationofa“picture”–asetofnumbersinterpretedbythecomputerwhichcreatesavisualrepresentationthatisunderstoodbyhumans.25525519914397187321234232211244198179123941953243521332112532172346818597131227111426Graphics?3TypeofImageColorScaleNumberFileFormatDimension4binarygraycolor5ColorofImageColorSystem(model)RGB模型HIS模型YIQ,YUV,HSV,CMYK,HSL…6TrueColorandPseudocolor24truecolorand32truecolorPseudoclor:Thecolorwegivetoaimagetoshowtheinformation.inwhichdifferentcolorlevelrepresentdifferentdata.7Whatisgray

GrayScalepixelvaluesrepresentalevelofgraynessorbrightness,rangingfromcompletelyblacktocompletelywhite.Inan8-bitGrayScaleimage,apixelwithavalueof0iscompletelyblack,andapixelwithavalueof255iscompletelywhite.Avalueof127representsagraycolorexactlyhalfwaybetweenblackandwhite(medium-gray),andapixelvalueof64hasagraycolorhalfwaybetweenmedium-grayandblack.

8ScaleNumberGreylevel

Weusegreyleveltorepresentbrightnessinformationinapicture.Ifonepictureonlyhave2purecolors:whiteandblack,itsinformationisverylimited.Toshowmoreinformation,wecanadoptgreyImage,thatUsuallyis6greyscale(26,64level)or8greyscale(28,256level).9256shadesofgray4grayscale6grayscale8grayscaleAlthoughGrayScaleimageswithbitdepthsof2,4,6,12,16and32exist,8BitGrayScaleimagesarethemostcommon.Thisisfortworeasons:1)its1-byte-per-pixelsizemakesiteasytomanipulatewithacomputer,and2)itcanfaithfullyrepresentanygrayscaleimagebecauseitprovides256distinctlevelsofgray(thehumaneyecandistinguishlessthan200graylevels).10FileFormatBMP:微软Windows设置的标准图像格式GIF:GraphicInterchangeFormat图形交换格式JPEG:JointPhotographicExpertGroupTIF:JPEG2000:DICOM文件计算机中存储图像文件的格式。面向对象统一标识符标签与属性1112BasicConceptionofImageBrightnessIntensityContrastGray(GrayLevel)DefinitionResolutionCoordinateHueSaturationColorTemperature13Pixelsareidentifiedbytheirpositioninagrid(two-dimensionalarray),referencedbyitsrow(x),andcolumn(y).CoordinateSystemImage:Pixelarray14数字图像的形成信号转换过程感知抽样量化15图像感知和获取16Example取样(Sampling)和量化(Quantization)17ImageProcessionTechnology图像的点运算图像的几何变换图像的正交变换图像的边缘检测与轮廓提取图像的形态学处理图像的增强图像分割图像复原图像重建图像测量与分析181.对比度增强灰度变换法直方图调整法Producehighercontrast（对比度）thantheoriginalby:

darkeningthelevelsbelowmintheoriginalimage

Brighteningthelevelsabovemintheoriginalimage19灰度变换法灰度变换法：这些处理方式都是针对原始图像的每一个像素直接对其灰度进行处理的，其处理过程主要是通过增强函数对像素的灰度级进行运算并将运算结果作为该像素的新灰度值来实现的。通过改变选用的增强函数的解析表达式就可以得到不同的处理效果，这类处理方法比较灵活方便，处理效果也不错。20灰度线性变换

DotOperationf(x)=ax+b灰度的线性变换a是函数的斜率，b是函数在有y上的截距，当a>1,输出图象对比度增加a<1,输出图象对比度减小。a=1且b<>0整体图象变亮或变暗。如果a=-1，b=255，整个图象反转。21LowdynamicrangeMediumcontrastFulldynamicrangeGoodcontrastGrayStretch22非线性变换分段函数对数变换LogTransformations指数变换Power-LawTransformations23分段线性变换函数对比拉伸实例24(幂变换)Power-LawTransformations25γ<1Power-LawTransformations26直方图HistogramDefinition:Histogramofadigitalimagewithgraylevelsintherange[0,L-1]isadiscretefunctionh(rk)=nk

rk

:k级灰度(thekthgraylevel)

nk

:灰度级为rk

的像素个数（thenumberofpixelsintheimagehavinggraylevelrk）27直方图

(Histogram)处理直方图拉伸直方图均衡化直方图匹配直方图(Histogram)处理是通过改变原始图像各像素在各灰度级上的概率分布来实现的。因此该直方图函数实际是图像的各灰度级的分布情况的反映，换句话说也就是给出了该幅图像所有灰度值的整体描述。通过该函数可以清楚地了解到图像对应的动态范围情况，可以了解到图像灰度的主要集中范围。28LowdynamicrangeMediumcontrastFulldynamicrangeGoodcontrastHistogramStretch（直方图的拉伸）29HistogramEqualization（直方图均衡化）

直方图均衡化处理的中心思想是把原始图像的灰度直方图从比较集中的某个灰度区间变成在全部灰度范围内的均匀分布。对图像空间域点的增强过程是通过增强函数T（r）来完成的。

30离散图像直方图均衡化——例

h(rk)03122434415164718293pr(rk)00.1210.0820.1630.1640.0450.0460.1670.0480.0890.1231离散图像直方图均衡化——例3）计算图像各灰度级的累计分布S。pr(rk)00.1210.0820.1630.1640.0450.0460.1670.0480.0890.1200.1210.2020.3630.5240.5650.6060.7670.8080.8891.0032离散图像直方图均衡化——例4）求出新图像g的灰度值。13998