image processing An image is a visual representation of something. It can be two-dimensional, three-dimensional, or somehow otherwise feed into the visual system to convey information. An image can be an artifact, such as a photograph or other two-dimensiona ...

, normalization is a process that changes the range of pixel intensity values. Applications include photographs with poor contrast due to glare, for example. Normalization is sometimes called contrast stretching or

histogram A histogram is an approximate representation of the distribution of numerical data. The term was first introduced by Karl Pearson. To construct a histogram, the first step is to " bin" (or "bucket") the range of values—that is, divide the ent ...

stretching. In more general fields of data processing, such as

digital signal processing Digital signal processing (DSP) is the use of digital processing, such as by computers or more specialized digital signal processors, to perform a wide variety of signal processing operations. The digital signals processed in this manner are ...

, it is referred to as dynamic range expansion. The purpose of dynamic range expansion in the various applications is usually to bring the image, or other type of signal, into a range that is more familiar or normal to the senses, hence the term normalization. Often, the motivation is to achieve consistency in dynamic range for a set of data, signals, or images to avoid mental distraction or fatigue. For example, a newspaper will strive to make all of the images in an issue share a similar range of grayscale. Normalization transforms an n-dimensional grayscale image

I:\\rightarrow\

with intensity values in the range

(\text,\text)

, into a new image

I_N:\\rightarrow\

with intensity values in the range

(\text,\text)

. The linear normalization of a grayscale

digital image A digital image is an image composed of picture elements, also known as ''pixels'', each with ''finite'', '' discrete quantities'' of numeric representation for its intensity or gray level that is an output from its two-dimensional functions ...

is performed according to the formula :

I_N=(I-\text)\frac+\text

For example, if the intensity range of the image is 50 to 180 and the desired range is 0 to 255 the process entails subtracting 50 from each of pixel intensity, making the range 0 to 130. Then each pixel intensity is multiplied by 255/130, making the range 0 to 255. Normalization might also be non linear, this happens when there isn't a linear relationship between

I

and

I_N

. An example of non-linear normalization is when the normalization follows a sigmoid function, in that case, the normalized image is computed according to the formula :

I_N=(\text-\text)\frac+\text

Where

\alpha

defines the width of the input intensity range, and

\beta

defines the intensity around which the range is centered.ITK Software Guide
/ref> Auto-normalization in image processing software typically normalizes to the full dynamic range of the number system specified in the image file format.

References

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External links

Contrast Stretching
Image processing

See also

References

External links