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Line 3 loads the library, line 4 reads the image, and Line 5 displays it. 5. In line 3, the package is loaded. In lines 4 and 5 the image is read and displayed, respectively. 4 Code presenting how to read jpeg images into R 1 2 3 4 5 > > > > > ✝ ✡ # R e a d i n g jpeg images library ( ReadImages ) draw <- read . jpeg ( " Draw . 5 Code presenting how to read PNG images into R 1 2 3 4 5 > > > > > ✝ ✡ # R e a d i n g png i m a g e s l i b r a r y ( png ) draw <- r e a d P N G ( " Draw . png " ) plot ( i m a g e m a t r i x ( draw )) ✆ In the case of TIFF images, the rtiff package must be used, which provides the readTiff function.

A modern introduction to probability and statistics: understanding why and how. London: Springer. Frery, A. , Lucca, E. D. , Freitas, C. C. & Sant’Anna, S. J. S. (1999). SAR segmentation algorithms: A quantitative assessment, in: International geoscience and remote sensing symposium: remote sensing of the system earth—A Challenge for the 21st Century, IEEE, pp. 1–3, IEEE Computer Society CD-ROM, Hamburg, Germany. Gonzalez, R. , & Woods, R. E. (1992). Digital image processing. MA: Addison-Wesley.

Frery and T. 1007/978-1-4471-4950-7_2, © Alejandro C. Frery 2013 21 22 2 Image Data Formats and Color Representation In color image analysis three attributes are used to differentiate one color from another: brightness, hue and saturation. , it is responsible for verifying the color, in the complete spectrum, from red to violet, and magenta. , it defines the “purity” of the color. High values of saturation result in more gray-scale pixels and small values result in pixels with high “purity”. For instance, the red color is highly saturated and the pink color is unsaturated.

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