Image normalization is a common image processing technique that is used to adjust the pixel values of an image to a standardized range. This is done in order to make the image more suitable for analysis and to remove any variations in brightness and contrast that might interfere with image processing tasks.
There are various methods of image normalization, but a common approach involves scaling the pixel values so that they fall within a certain range, such as 0 to 1 or -1 to 1. This can be done by subtracting the minimum pixel value from all pixels and then dividing by the range (the difference between the maximum and minimum values). This ensures that the pixel values are within the desired range and that they are evenly distributed across that range.
Other techniques for image normalization include histogram equalization, which adjusts the brightness and contrast of the image to make it more uniform, and adaptive normalization, which adjusts the normalization parameters based on the local characteristics of the image.
There are various methods of image normalization, but a common approach involves scaling the pixel values so that they fall within a certain range, such as 0 to 1 or -1 to 1. This can be done by subtracting the minimum pixel value from all pixels and then dividing by the range (the difference between the maximum and minimum values). This ensures that the pixel values are within the desired range and that they are evenly distributed across that range.
Other techniques for image normalization include histogram equalization, which adjusts the brightness and contrast of the image to make it more uniform, and adaptive normalization, which adjusts the normalization parameters based on the local characteristics of the image.
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