|Image Processing Toolbox User's Guide|
Adjusting Intensity Values to a Specified Range
You can adjust the intensity values in an image using the
imadjust function, where you specify the range of intensity values in the output image.
For example, this code increases the contrast in a low-contrast grayscale image by remapping the data values to fill the entire intensity range [0, 255].
This figure displays the adjusted image and its histogram. Notice the increased contrast in the image, and that the histogram now fills the entire range.
Adjusted Image and Its Histogram
Specifying the Adjustment Limits
You can optionally specify the range of the input values and the output values using
imadjust. You specify these ranges in two vectors that you pass to
imadjust as arguments. The first vector specifies the low- and high-intensity values that you want to map. The second vector specifies the scale over which you want to map them.
Note that you must specify the intensities as values between 0 and 1 regardless of the class of |
For example, you can decrease the contrast of an image by narrowing the range of the data. In the example below, the man's coat is too dark to reveal any detail.
imadjust maps the range [0,51] in the
uint8 input image to [128,255] in the output image. This brightens the image considerably, and also widens the dynamic range of the dark portions of the original image, making it much easier to see the details in the coat. Note, however, that because all values above 51 in the original image are mapped to 255 (white) in the adjusted image, the adjusted image appears washed out.
Image After Remapping and Widening the Dynamic Range
Setting the Adjustment Limits Automatically
imadjust, you must typically perform two steps:
For a more convenient way to specify these limits, use the
stretchlim function. (The
imadjust function uses
stretchlim for its simplest syntax,
This function calculates the histogram of the image and determines the adjustment limits automatically. The
stretchlim function returns these values as fractions in a vector that you can pass as the
[low_in high_in] argument to
imadjust; for example:
stretchlim uses the intensity values that represent the bottom 1% (0.01) and the top 1% (0.99) of the range as the adjustment limits. By trimming the extremes at both ends of the intensity range,
stretchlim makes more room in the adjusted dynamic range for the remaining intensities. But you can specify other range limits as an argument to
stretchlim. See the
stretchlim reference page for more information.
top. By default, the values between
high are mapped linearly to values between
top. For example, the value halfway between
high corresponds to the value halfway between
imadjust can accept an additional argument that specifies the gamma correction factor. Depending on the value of gamma, the mapping between values in the input and output images might be nonlinear. For example, the value halfway between
high might map to a value either greater than or less than the value halfway between
Gamma can be any value between 0 and infinity. If gamma is 1 (the default), the mapping is linear. If gamma is less than 1, the mapping is weighted toward higher (brighter) output values. If gamma is greater than 1, the mapping is weighted toward lower (darker) output values.
The figure below illustrates this relationship. The three transformation curves show how values are mapped when gamma is less than, equal to, and greater than 1. (In each graph, the x-axis represents the intensity values in the input image, and the y-axis represents the intensity values in the output image.)
Plots Showing Three Different Gamma Correction Settings
The example below illustrates gamma correction. Notice that in the call to
imadjust, the data ranges of the input and output images are specified as empty matrices. When you specify an empty matrix,
imadjust uses the default range of [0,1]. In the example, both ranges are left empty; this means that gamma correction is applied without any other adjustment of the data.
[X,map] = imread('forest.tif') I = ind2gray(X,map); J = imadjust(I,,,0.5); imshow(I) figure, imshow(J)
Image Before and After Applying Gamma Correction
|Intensity Adjustment||Histogram Equalization|
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