Color Image Processing

Color Image Processing

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RGB image • RGB image represents each pixel color as a set of three values, representing the red, green, and blue intensities that make up the color. • The RGB image range values are [0,1] and [0,255] for class double, uint8 respectively.

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Example RGB

R-Component

Original Image

G-Component

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B-Component

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The RGB Color Model If R,G, and B are represented with 8 bits (24-bit RGB image), the total number of colors is (28 )3=16,777,216

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Primary and secondary colors • primary colors:        R – red         G – green        B – blue • Secondary colors  M – magenta (= red + blue)        C – cyan (= green + blue)       Y – yellow (= red + green)   Color and wavelet

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Indexed Image • An indexed image is where the pixel values are indices to elements in a colour map or colour lookup table. • Index image has two components: a data matrix of images and color map matrix.

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Displaying indexed images >> I2=I(:,:,2); % green values of I considers I2 as an indexed >> image(I2)Matlab image as it doesn’t contain entries for >> colorbar % display colourmap Index Associate d color Colour Looku p Table

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Displaying indexed images (continued)

• change colourmap >> colormap(gray) Type >>help graph3d to get a list of built-in colourmaps. Experiment with different built-in colourmaps. Define your own colourmap mymap by creating a matrix (size m x 3 ) with red, green, blue entries. Display an image using your colourmap.

• scale colourmap >> imagesc(I2)

Red =1.0, Green = 1.0, Blue =1.0, corresponds to index 64 Red =0.0, Green = 0.0, Blue = 0.0, corresponds to index 1 Red =1.0, Green = 1.0, Blue =1.0, corresponds to index 255 Red =0.0, Green = 0.0, Blue = 0.0, corresponds to index 0

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RGB values of basic color

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IPT Functions for converting between RGB, Indexed, and gray scale intensity images

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Converting to other color spaces • • • • •

NTSC color spaces The YCbCr color space The HSV color space The CMY and CMYK spaces The HSI color spaces

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The HSI Color Model • Hue—the color • Saturation—the amount of white that is mixed with the hue • Intensity—expresses the brightness or luminance of the chromaticity (=hue and saturation)

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Brightness, Hue, and Saturation • Brightness is a synonym of intensity • Hue represents the impression related to the dominant wavelength of the color stimulus • Saturation expresses the relative color purity (amount of white light in the color) • Hue and Saturation taken together are called the chromaticity coordinates (polar system) • Matlab conversion function: rgb2hsv

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HSI Color Model

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Converting from RGB to HSI

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Example HSI

Hue

Original Image

Saturation

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Intensity

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Spacial Filtering of color images • The spacial filtering concentrating mostly on RGB images. • And basic concepts are applicable to other color models • The two examples of linear filtering – Color image smoothing – Color image sharpening

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Spacial Filtering of color images(cont…) • The linear spacial filtering consists of the following steps – Extract the components images – Filter each components image individually. – Reconstruct the filtered RGB image

• In RGB color system, we consider color image sharpening using the Laplacian vector. Color and wavelet

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Wavelets • A wavelet is a waveform of effectively limited duration that has an average value of zero. • A wavelet transform is the representation of a function by wavelets. • The wavelets are scaled and translated copies of a finite-length or fast-decaying oscillating waveform . Color and wavelet

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Wavelets • Compare wavelets with sine waves, which are the basis of Fourier analysis. • Wavelet transforms are classified into discrete wavelet transforms (DWTs) and continuous wavelet transforms (CWTs).

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Wavelets • A discrete wavelet transform (DWT) is any wavelet transform for which the wavelets are discretely sampled. • Wavelet Toolbox provides two categories of tools: – Command line functions – Graphical interactive tools Waveinfo(wfamily) eg Waveinfo(‘haar’) Wavemenu Color and wavelet

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Fast Wavelet Transform • The Fast Wavelet Transform is algorithm designed to turn a waveform or signal in the time domain into a sequence of coefficients based on an orthogonal basis of small finite waves, or wavelets.

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Wavelet Toolbox FWT filters and filter family

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The Haar scaling and wavelet functions

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Wavelets in image processing • Compute the two dimensional wavelet transform of an image. • Alter the transform coefficients • Compute the inverse transform

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