[转载] Image Types

转载自https://www.mathworks.com/help/matlab/creating_plots/image-types.html

Image Types

Indexed Images

An indexed image consists of a data matrix, X, and a colormap matrix, mapmap is an m-by-3 array of class double containing floating-point values in the range [0, 1]. Each row of map specifies the red, green, and blue components of a single color. An indexed image uses “direct mapping” of pixel values to colormap values. The color of each image pixel is determined by using the corresponding value of X as an index into map. Values of X therefore must be integers. The value 1 points to the first row in map, the value 2 points to the second row, and so on. Display an indexed image with the statements

image(X); colormap(map)

A colormap is often stored with an indexed image and is automatically loaded with the image when you use the imread function. However, you are not limited to using the default colormap—use any colormap that you choose. The description for the property CDataMapping describes how to alter the type of mapping used.

The next figure illustrates the structure of an indexed image. The pixels in the image are represented by integers, which are pointers (indices) to color values stored in the colormap.

Indexed image and inset showing the pixel index values for a selected region and the mapping of one index to a color in the colormap

The relationship between the values in the image matrix and the colormap depends on the class of the image matrix. If the image matrix is of class double, the value 1 points to the first row in the colormap, the value 2 points to the second row, and so on. If the image matrix is of class uint8 or uint16, there is an offset—the value 0 points to the first row in the colormap, the value 1 points to the second row, and so on. The offset is also used in graphics file formats to maximize the number of colors that can be supported. In the preceding image, the image matrix is of class double. Because there is no offset, the value 5 points to the fifth row of the colormap.

Grayscale (Intensity) Images

A grayscale image, sometimes referred to as an intensity image, is a data matrix I whose values represent intensities within some range. A grayscale image is represented as a single matrix, with each element of the matrix corresponding to one image pixel. The matrix can be of class doubleuint8, or uint16. While grayscale images are rarely saved with a colormap, a colormap is still used to display them. In essence, grayscale images are treated as indexed images.

This figure depicts a grayscale image of class double.

Grayscale image and inset showing the pixel values for a selected region

To display a grayscale image, use the imagesc (“image scale”) function, which enables you to set the range of intensity values. imagesc scales the image data to use the full colormap. Use the two-input form of imagesc to display a grayscale image, for example:

imagesc(I,[0 1]); colormap(gray);

The second input argument to imagesc specifies the desired intensity range. The imagesc function displays I by mapping the first value in the range (usually 0) to the first colormap entry, and the second value (usually 1) to the last colormap entry. Values in between are linearly distributed throughout the remaining colormap colors.

Although it is conventional to display grayscale images using a grayscale colormap, it is possible to use other colormaps. For example, the following statements display the grayscale image I in shades of blue and green:

imagesc(I,[0 1]); colormap(winter);

To display a matrix A with an arbitrary range of values as a grayscale image, use the single-argument form of imagesc. With one input argument, imagesc maps the minimum value of the data matrix to the first colormap entry, and maps the maximum value to the last colormap entry. For example, these two lines are equivalent:

imagesc(A); colormap(gray)
imagesc(A,[min(A(:)) max(A(:))]); colormap(gray)

RGB (Truecolor) Images

An RGB image, sometimes referred to as a truecolor image, is stored as an m-by-n-by-3 data array that defines red, green, and blue color components for each individual pixel. RGB images do not use a palette. 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. Graphics file formats store RGB images as 24-bit images, where the red, green, and blue components are 8 bits each. This yields a potential of 16 million colors. The precision with which a real-life image can be replicated has led to the nickname “truecolor image.”

An RGB MATLAB® array can be of class doubleuint8, or uint16. In an RGB array of class double, each color component is a value between 0 and 1. A pixel whose color components are (0,0,0) is displayed as black, and a pixel whose color components are (1,1,1) is displayed as white. The three color components for each pixel are stored along the third dimension of the data array. 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.

To display the truecolor image RGB, use the image function:

image(RGB)

The next figure shows an RGB image of class double.

RGB color image and inset showing the red, green, and blue pixel values for a selected region

To determine the color of the pixel at (2,3), look at the RGB triplet stored in (2,3,1:3). Suppose (2,3,1) contains the value 0.5176, (2,3,2) contains 0.1608, and (2,3,3) contains 0.0627. The color for the pixel at (2,3) is

0.5176 0.1608 0.0627

posted on 2022-10-21 15:58  无声烟雨  阅读(22)  评论(0编辑  收藏  举报

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