![]() ![]() The black region in the image shows pixel values that contain no red values, i.e., R = 0. As red becomes mixed with green or blue, gray pixels appear. ![]() For example, in the Red Plane image, the white represents the highest concentration of pure red values. The white corresponds to the highest values (purest shades) of each separate color. Notice that each separated color plane in the figure contains an area of white. RGB=reshape(ones(64,1)*reshape(jet(64),1,192),) įigure 2-5: The Separated Color Planes of an RGB Image.It displays each color plane image separately, and also displays the original image. To further illustrate the concept of the three separate color planes used in an RGB image, the code sample below creates a simple RGB image containing uninterrupted areas of red, green, and blue, and then creates one image for each of its separate color planes (red, green, and blue). To determine the color of the pixel at (2,3), you would look at the RGB triplet stored in (2,3,1:3). For example, the red, green, and blue color components of the pixel (10,5) are stored in RGB(10,5,1), RGB(10,5,2), and RGB(10,5,3), respectively.įigure 2-4 depicts an RGB image of class double.įigure 2-4: The Color Planes of an RGB Image The three color components for each pixel are stored along the third dimension of the data array. A pixel whose color components are (0,0,0) displays as black, and a pixel whose color components are (1,1,1) displays as white. In an RGB array of class double, each color component is a value between 0 and 1. The precision with which a real-life image can be replicated has led to the commonly used term truecolor image.Īn RGB MATLAB array can be of class double, uint8, or uint16. This yields a potential of 16 million colors. 1)First, determine the color space of the image data you are working with if you have RGB values, convert them to the corresponding color space, such as CIE XYZ or CIE LAB 2)Once you have the color values in a suitable color space, you can map them to the visible spectrum. Graphics file formats store RGB images as 24-bit images, where the red, green, and blue components are 8 bits each. The color of each pixel is determined by the combination of the red, green, and blue intensities stored in each color plane at the pixel's location. Note that MATLAB assumes that for uint8 images the values are between 0 and 255, while for double images, the values are between 0 and 1, so they would need to be scaled.Introduction (Image Processing Toolbox) Image Processing ToolboxĪn RGB image, sometimes referred to as a truecolor image, is stored in MATLAB as an m-by-n-by-3 data array that defines red, green, and blue color components for each individual pixel. To have a lossless conversion, you should use the double datatype. For a testimage of mine, the maximum difference between RGB and RGB1 was max(abs(RGB(:)-RGB1(:))) ![]() Note that if you are using uint8 as type for RGB, then YCBCR and YUV will be uint8 too and the conversion will be lossy. To convert an RGB image to YUV, you can thus use RGB = imread('11111.bmp') To convert between RGB and YCbCr, MATLAB offers the functions rgb2ycbcr and ycbcr2rgb. ![]()
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