Image Histograms and applications - Computer Science at Rutgers
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Image Histograms and applications - Computer Science at Rutgers
Digitizing images What is projected on the image plan is a distribution of light energy that is:
Two-dimensional Time-dependent Continuous
To go digital: Spatial sampling Temporal sampling Quantization of pixel values
Digital image: two-dimensional, ordered matrix of integers, i.e., a two-dimensional function of integer coordinates NxN that maps a range of image values P
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Image resolution: number of image elements per measurement. Image coordinate system
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Image Histograms Histograms are used to depict image statistics in an easily interpreted visual format Useful during image capturing: now already in digital cameras Used to improve the visual appearance of an image Can also be used to determine what type of processing has been applied to an image.
Image histogram: describes the frequency of the intensity values that occur in an image
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Histograms don’t encode information about the spatial arrangement of pixels in the image We cannot reconstruct an image given only it’s histogram
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Interpreting Histograms Histograms depicts problems that originate during image acquisition Exposure, contrast, dynamic range
Histograms can be used to detect a wide range of image defects: saturation, spikes and gaps, impact of image compression
Histograms and Exposure
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Histogram and Contrast
Dynamic Range
Dynamic Range: the number of distinct pixel value in an image
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Detecting Image Defects There is no ideal or optimal histogram shape. It depends on the image and on the application Image Defects: Saturation: the illumination values lying outside of the sensor’s range are mapped to its maximum or minimum values: spike at the tails Spikes and Gaps in manipulated images. Why? Impact of image compression
Histograms show the impacts of image compression Ex: in GIF compression, the dynamic range is reduced to only few intensities (quantization)
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Ex: JPEG compression on a line graphics.
JPEG compression
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Computing Histograms
Histograms of images with more than 8 bits: Binning
Ex: B=256 for 14 bit image K=16384, bin width = 64
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Color Image Histograms
Color Image Histograms For color images, two kind of histograms: Intensity histogram Individual Color Channel Histograms
Both provides useful information about lighting, contrast, dynamic range and saturation effects for individual color components They provide no information about the actual color distribution!