tailieunhanh - Lecture Digital image processing - Lecture 23: Color Images

This chapter presents the following content: Color image processing, primary and secondary colors, color characteristics, chromaticity diagram and its use, color models, rgb color model, image registration, different mismatch or measures, cross correlation between tow images, applications of image registration. | Digital Image Processing CSC331 Color Image Processing 1 Summery of previous lecture Image registration Different mismatch or measures Cross correlation between tow images Applications of image registration 2 Todays lecture Color image processing Primary and secondary colors Color characteristics Chromaticity diagram and its use Color models RGB color model 3 Color Fundamentals The human visual system can distinguish hundreds of thousands of different color shades and intensities, but only around 100 shades of grey. Therefore, in an image, a great deal of extra information may be contained in the color, and this extra information can then be used to simplify image analysis, . object identification and extraction based on color. When color is available, it gives much more information about an image than intensity alone. Color is very useful for recognition of objects in an image both for humans and computers. Types of color renderings True-color or full color An image is called a "true-color" image when it offers a natural color rendition, or when it comes close to it. This means that the colors of an object in an image appear to a human observer the same way as if this observer were to directly view the object: A green tree appears green in the image, a red apple red, a blue sky blue, and so on 5 Types of color renderings False-color image sacrifices natural color rendition in order to ease the detection of features that are not readily discernible otherwise – for example the use of near infrared for the detection of vegetation in satellite images 6 7 Types of color renderings Pseudo color image is derived from a grayscale image by mapping each intensity value to a color according to a table or function. Pseudo color is typically used when a single channel of data is available (. temperature, elevation, soil composition, tissue type, and so on), in contrast to false color which is commonly used to display three channels of data. A typical example for the | Digital Image Processing CSC331 Color Image Processing 1 Summery of previous lecture Image registration Different mismatch or measures Cross correlation between tow images Applications of image registration 2 Todays lecture Color image processing Primary and secondary colors Color characteristics Chromaticity diagram and its use Color models RGB color model 3 Color Fundamentals The human visual system can distinguish hundreds of thousands of different color shades and intensities, but only around 100 shades of grey. Therefore, in an image, a great deal of extra information may be contained in the color, and this extra information can then be used to simplify image analysis, . object identification and extraction based on color. When color is available, it gives much more information about an image than intensity alone. Color is very useful for recognition of objects in an image both for humans and computers. Types of color renderings True-color or full color An image is called a .