Unit 17 Images and Televisions,Unit 17 Images and Televisions,Passage A Fundamental Concepts,Passage B Compression/Decompression Techniques,Passage C Television,Passage A Digital Image Fundamentals,1.Digital Image Resolution,A digital image is made up of many rows and columns of pixels.For gray scale images,each pixel is assigned a number that represents the gray shade assigned to that pixel.The larger the number of pixels in an image,and the larger the number of available gray scale levels,the better the resolution of the image.Figure 17.1 is an 17-bit images,with 2,17,256 possible gray scale levels.The number of row and column are 303228.,Figure 17.1 An 30322817 Digital Image,2.Histograms,The gray scales present in a digital image can be summarized by its histogram(see Figure 17.2)The histogram reports the number of pixels for each grayscale level present in the image,as a bar graph.When an image uses only a small portion of the available gray scale levels,histogram equalization can be used to spread out the usage of gray scale levels over the entire available range,1,This procedure re-assigns gray scale levels so that image contrast is improved.,Figure 17.2 A Histogram,3.Addition and Subtraction of Images,Digital images can be added and subtracted pixel-by-pixel.Adding two images can combine two sets of objects into a single image.Moreover,several noisy images of the same scene can be averaged together to reduce the effect of noise.Image subtraction,on the other hand,can be used to remove an unwanted background from an image.Subtraction of two time-lapsed photographs will show where motion has occurred between the two.,When two images are added or subtracted,the resultant matrix will frequently contain illegal gray scale values.For example,when a pixel in one 17-bit image has the gray scale level 129 and the corresponding pixel in a second 17-bit image has the gray scale level 201,the sum pixel is 129+201330.This is outside the legal range for an 17-bit image,which may only contain gray scale levels between 0 and 255.When the same two images are subtracted,the difference pixel is 129-201=-72,again a value outside the legal range.For these reasons,scaling follows most image arithmetic.Scaling to the range 0,GSL,max,may be accomplished as follows:,4.Warping and Morphing,Warping and morphing are digital image techniques that are finding application not only in entertainment but also in medical imaging.Warping stretches or re-shapes an object in an image,while morphing transforms one image into another.These transformations may be accomplished by marking control points,control lines,or triangles in a source image and choosing their new positions in a destination image.The transition between source and destination images is then accomplished by smoothly transforming not only the control element locations,but also their colors.The locations and colors of pixels not explicitly marked as control elements are determined by the locations and colors of the control elements that are nearest.,5.Image Filtering,Digital images can be filtered using two-dimensional convolution with a convolution kernel.When an,N,N,image is filtered by an,M,M,convolution kernel,(,M,-1/2)rows and columns on each side of the image are lost to boundary effects.Low pass filters blur images,high pass filters emphasize sharp changes in gray scale level,and edge filters locate edges in an image.,2,6.Dilation and Erosion,Dilation adds a layer of pixels to all objects in an image.Erosion removes one layer of pixels from all objects.When dilation is followed by erosion,gaps in broken boundaries,identified through edge detection can be filled in.Conversely,when erosion is followed by dilation,spots of noise in an image are removed.,Successfully detecting the edges in an image is the first step towards confident identification of object boundaries and then objects recognition.From boundary information,shape characteristics like perimeter and area can be calculated,which can be used to classify an object.,7.Image Spectra ,Two-dimensional FFTs are used to analyze the spectra of digital images.Just as in the one-dimensional case,a two-dimensional spectrum comprises a magnitude spectrum and a phase spectrum.The phase spectrum carries the best information about the locations of the objects in the image.,3,When all magnitudes are set to one,the phases alone still show a facsimile of the original image.When all phases are set to zero,the magnitudes alone show no trace of it.,Image spectra form the basis for both CT(computed tomography)and MRI(magnetic resonance imaging)scan displays.CT scans are X-rays taken in many directions in a single plane of an object.,4,MRI scans depend instead on the magnetic properties of an object placed in a varying magnetic field.Both types of scans permit non-invasive investigations of three-dimensional objects.,8.Image compression,In part due to the Internet,digital images are transmitted from place to place more often than e