Last Time Course introduction Assignment 1 not graded but necessary View is part of Project 1 Image and film basics 1 24 02 University of Wisconsin CS559 Spring 2002 Today More on Digital Images Introduction to color Homework 1 1 24 02 University of Wisconsin CS559 Spring 2002 Digital Images Computers work with discrete pieces of information How do we digitize a continuous image Break the continuous space into small areas pixels Use a single value for each pixel the pixel value no color yet No longer continuous in space or intensity This process is fraught with danger as we shall see Continuous Discrete Pixels Picture Elements 1 24 02 University of Wisconsin CS559 Spring 2002 Digital Cameras CCD stores a charge each time a photon hits it Bins have discrete area one per pixel Spatially discrete Camera reads the charges out of the bins at some frequency Convert charges to discrete value Discrete in intensity Store values in memory the image Still have issues of motion blur depth of field dynamic range etc 1 24 02 University of Wisconsin CS559 Spring 2002 Light in Lens CCD Alternative Imaging Methods We obviously don t have to use a digital camera to generate a digital image You can write the pixels directly or use a paint program or describe a 3D scene and have a computer render it into an image or This course is all about these other methods However it still helps to think of any digital image as a sample of some ideal image 1 24 02 University of Wisconsin CS559 Spring 2002 Discretization Issues Can only store a finite number of pixels Resolution Pixels per inch or dpi dots per inch from printers Storage space goes up with square of resolution 600dpi has 4 more pixels than 300dpi Can only store a finite range of intensity values Typically referred to as depth number of bits per pixel Directly related to the number of colors available Also concerned with the minimum and maximum intensity dynamic range Both film and digital cameras have highly limited dynamic range The big question is What is enough resolution and enough depth 1 24 02 University of Wisconsin CS559 Spring 2002 Perceptual Issues Humans can discriminate about a minute of arc At fovea so only in center of view 20 20 vision At 1m about 0 2mm Dot Pitch of monitors Limits the required number of pixels Humans can discriminate about 8 bits of intensity 129 128 125 Just Noticeable Difference experiments Limits the required depth for typical dynamic ranges Actually it s 9 bits but 8 is far more convenient BUT while perception can guide resolution requirements for display when manipulating images much higher resolution may be required 1 24 02 University of Wisconsin CS559 Spring 2002 Intensity Perception Humans are actually tuned to the ratio of intensities not their absolute difference So going from a 50 to 100 Watt light bulb looks the same as going from 100 to 200 So if we only have 4 intensities between 0 and 1 we should choose to use 0 0 25 0 5 and 1 Most computer graphics ignores this giving poorer perceptible intensity resolution at low light levels and better resolution at high light levels It would use 0 0 33 0 66 and 1 1 24 02 University of Wisconsin CS559 Spring 2002 High range low res Image depth refers to the number of bits available but not how those bits map onto intensities We can use those bits to represent a large range at low resolution or a small range at high resolution Common display devices can only show a limited dynamic range so typically we fix the range at that of the display device and choose high resolution Low range high res Dynamic Range All possible intensities 1 24 02 University of Wisconsin CS559 Spring 2002 More Dynamic Range Real scenes have very high and very low intensities Humans can see contrast at very low and very high light levels Can t see all levels all the time use adaptation to adjust Still high range even at one adaptation level Film has low dynamic range 100 1 Monitors are even worse Many ways to deal with the problem but no great solution Way beyond the scope of this course 1 24 02 University of Wisconsin CS559 Spring 2002 Display on a Monitor When images are created a linear mapping between pixels and intensity is assumed For example if you double the pixel value the displayed intensity should double Monitors however do not work that way For analog monitors the pixel value is converted to a voltage The voltage is used to control the intensity of the monitor pixels But the voltage to display intensity is not linear Same problem with digital monitors they just do the pixel to intensity conversion differently The outcome A linear intensity scale in memory does not look linear on a monitor 1 24 02 University of Wisconsin CS559 Spring 2002 Gamma Control The mapping from voltage to display is usually an exponential function I display I to monitor To correct the problem we pass the pixel values through a gamma function before converting them to the monitor I to monitor I 1 image This process is called gamma correction The parameter is controlled by the user It should be matched to a particular monitor Typical values are between 2 2 and 2 5 The mapping can be done in hardware or software 1 24 02 University of Wisconsin CS559 Spring 2002 Some Facts About Color So far we have only discussed intensities so called achromatic light black and white Accurate color reproduction is commercially valuable e g Kodak yellow painting a house Of the order of 10 color names are widely recognized by English speakers other languages have fewer more but not much more Color reproduction problems have been increased by the prevalence of digital imaging eg digital libraries of art Color consistency is also important in user interfaces eg what you see on the monitor should match the printed version 1 24 02 University of Wisconsin CS559 Spring 2002 Light and Color The frequency of light determines its color Frequency wavelength energy all related Describe incoming light by a spectrum Intensity of light at each frequency Just like a graph of intensity vs frequency We care about wavelengths in the visible spectrum between the infra red 700nm and the ultra violet 400nm 1 24 02 University of Wisconsin CS559 Spring 2002 White Photons White Less Intense White grey Wavelength nm 400 500 600 700 Note that color and intensity are technically two different things However in common usage we use color to refer to both For example dark red vs light red You will have to use context to extract the meaning 1 24 02
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