- Digital Image Processing
- DIP - Home
- DIP - Image Processing Introduction
- DIP - Signal and System Introduction
- DIP - History of Photography
- DIP - Applications and Usage
- DIP - Concept of Dimensions
- DIP - Image Formation on Camera
- DIP - Camera Mechanism
- DIP - Concept of Pixel
- DIP - Perspective Transformation
- DIP - Concept of Bits Per Pixel
- DIP - Types of Images
- DIP - Color Codes Conversion
- DIP - Grayscale to RGB Conversion
- DIP - Concept of Sampling
- DIP - Pixel Resolution
- DIP - Concept of Zooming
- DIP - Zooming methods
- DIP - Spatial Resolution
- DIP - Pixels Dots and Lines per inch
- DIP - Gray Level Resolution
- DIP - Concept of Quantization
- DIP - ISO Preference curves
- DIP - Concept of Dithering
- DIP - Histograms Introduction
- DIP - Brightness and Contrast
- DIP - Image Transformations
- DIP - Histogram Sliding
- DIP - Histogram Stretching
- DIP - Introduction to Probability
- DIP - Histogram Equalization
- DIP - Gray Level Transformations
- DIP - Concept of convolution
- DIP - Concept of Masks
- DIP - Concept of Blurring
- DIP - Concept of Edge Detection
- DIP - Prewitt Operator
- DIP - Sobel operator
- DIP - Robinson Compass Mask
- DIP - Krisch Compass Mask
- DIP - Laplacian Operator
- DIP - Frequency Domain Analysis
- DIP - Fourier series and Transform
- DIP - Convolution theorm
- DIP - High Pass vs Low Pass Filters
- DIP - Introduction to Color Spaces
- DIP - JPEG compression
- DIP - Optical Character Recognition
- DIP - Computer Vision and Graphics
- DIP Useful Resources
- DIP - Quick Guide
- DIP - Useful Resources
- DIP - Discussion
- Selected Reading
- UPSC IAS Exams Notes
- Developer's Best Practices
- Questions and Answers
- Effective Resume Writing
- HR Interview Questions
- Computer Glossary
- Who is Who
Introduction to Color Spaces
In this tutorial, we are going to talk about color spaces.
What are color spaces?
Color spaces are different types of color modes, used in image processing and signals and system for various purposes. Some of the common color spaces are:
RGB is the most widely used color space, and we have already discussed it in the past tutorials. RGB stands for red green and blue.
What RGB model states, that each color image is actually formed of three different images. Red image, Blue image, and black image. A normal grayscale image can be defined by only one matrix, but a color image is actually composed of three different matrices.
One color image matrix = red matrix + blue matrix + green matrix
This can be best seen in this example below.
Applications of RGB
The common applications of RGB model are
- Cathode ray tube (CRT)
- Liquid crystal display (LCD)
- Plasma Display or LED display such as a television
- A compute monitor or a large scale screen
RGB to CMY conversion
The conversion from RGB to CMY is done using this method.
Consider you have an color image , means you have three different arrays of RED, GREEN and BLUE. Now if you want to convert it into CMY, here’s what you have to do. You have to subtract it by the maximum number of levels – 1. Each matrix is subtracted and its respective CMY matrix is filled with result.
Y’UV defines a color space in terms of one luma (Y’) and two chrominance (UV) components. The Y’UV color model is used in the following composite color video standards.
NTSC ( National Television System Committee)
PAL (Phase Alternating Line)
SECAM (Sequential couleur a amemoire, French for “sequential color with memory)
Y’CbCr color model contains Y’, the luma component and cb and cr are the blue-difference and red difference chroma components.
It is not an absolute color space. It is mainly used for digital systems
Its common applications include JPEG and MPEG compression.
Y’UV is often used as the term for Y’CbCr, however they are totally different formats. The main difference between these two is that the former is analog while the later is digital.