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Mauromaiorca (talk | contribs) The article had major errors (i.e. normalization can be either linear or non-linear), there was just an example of linear normalization. |
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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]].<br />
Normalization process that transform a n-dimensional [[grayscale]] image <math>I:{1,.,n}\rightarrow\{\text{Min},..,\text{Max}\}</math> with intensity values in the range (Min,Max), into a new image <math>I_N:{1,.,n}\rightarrow\{\text{newMin},..,\text{newMax}\}</math> with intensity values in the range (newMin,newMax). <br />
The [[linear]] normalization of a [[grayscale]] [[digital image]] is performed according to the formula
:<math>I_N=(I-\text{Min})\frac{\text{newMax}-\text{newMin}}{\text{Max}-\text{Min}}+\text{newMin}</math>
Normalization might also be non linear, this happens when there isn't a [[linear]] relationship between <math>I</math> and <math>I_N</math>. 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
:<math>I_N=(\text{newMax}-\text{newMin})\frac{1}{1+e^{\frac{I-\beta}{\alpha}}}+\text{newMin}</math>
Where <math>\alpha</math> defines the width of the input intensity range, and <math>\beta</math> defines the intensity around which the range is centered <ref>[http://www.itk.org/ItkSoftwareGuide.pdf 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. <br />
▲Normalization is a [[linear]] process. 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. Auto-normalization in image processing software typically normalizes to the full dynamic range of the number system specified in the image file format.
The normalization process will produce iris regions, which have the same constant dimensions, so that two photographs of the same iris under different conditions will have characteristic features at the same spatial ___location.
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