# Converting to other color spaces

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Category: Education

## Presentation Description

digital image processing

## Presentation Transcript

### Converting to other color spaces:

C onvertin g to other color spaces By, G.Ramya ,

### Introduction:

Introduction RGB values are represented directly in an RGB image, or indirectly in an indexed image. A colormap is an m -by-3 matrix of real numbers between 0.0 and 1.0. Each row is an RGB vector that defines one color. The k th row of the colormap defines the k th color.

### Color space:

Color space However, there are other models besides RGB for representing colors numerically. The various models are referred to as color spaces because most of them can be mapped into a 2-D, 3-D, or 4-D coordinate system; thus, a color specification is made up of coordinates in a 2-D, 3-D, or 4-D space.

### Why color space?:

Why color space? they present color information in ways that make certain calculations more convenient or because they provide a way to identify colors that is more intuitive.

### Color spaces:

Color spaces NTSC YCbCr HSV CMY CMYK HSI

### NTSC color space:

NTSC color space The National Television Systems Committee (NTSC) defines a color space known as YIQ. This color space is used in televisions in the United States. One of the main advantages of this format is that grayscale information is separated from color data, so the same signal can be used for both color and black and white sets.

### Contd..:

Contd.. NTSC consists of three components: Luminance(Y), Hue(I), Saturation(Q). Luminance --  gray scale information I & Q -- RGB components.

### PowerPoint Presentation:

yiq_image =rgb2ntsc( rgb_image ) Output image M x N x 3 array class of double Input image Uint8,uint16, double. Yiq_image (:,:,1)=luminance Yiq_image (:,:,2)=hue Yiq_image (:,:,3)=saturation rgb_image =ntsc2rgb( yiq_image )

### YCbCr color space:

YCbCr color space Used in digital video. Y-luminance information Cb,Cr -color components Cb -difference bn the blue component and a reference value. Cr-difference bn the red component and a reference value.

### PowerPoint Presentation:

Ycbcr_image =rgb2cbcr( rgb_image ) rgb_image =cbcr2rgb( Ycbr_image ) o/p uint8,uint 16,double i /p- same calss of input image

### HSV color space:

HSV color space H-hue S-saturation V-value. As hue varies from 0 to 1.0, the corresponding colors vary from red through yellow, green, cyan, blue, magenta, and back to red. As saturation varies from 0 to 1.0, the corresponding colors (hues) vary from unsaturated (shades of gray) to fully saturated (no white component). As value, or brightness, varies from 0 to 1.0, the corresponding colors become increasingly brighter.

### PowerPoint Presentation:

Converting from RGB to HSV is mapping cartesian coordinates to cylinderical coordinates….

### PowerPoint Presentation:

hsv_image =rgb2hsv( rgb_image ); Uint8,uint16,double double

### CMY and CMYK color spaces:

CMY and CMYK color spaces C-cyan M-magenta Y-yellow (secondary colors of light)

### PowerPoint Presentation:

Cmy_image = imcomplement ( rgb_image )

### HSI color space:

HSI color space All the other models are not well suited for describing colors. hue- describes a pure color ( red,orange,yellow ) saturation- gives a measure of the degree to which a pure color is diluted by white light. Intensity- describes color sensation.

### HIS model:

HIS model Is an ideal tool for developing image-processing algorithms based on color descriptions.