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By Christian Demant
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In this case, only the absence of bright objects in the first image or the presence of additional dark ones can be detected. Linear scaling: As with addition, linear scaling to the possible range of gray level values is the most expensive method. e. the theoretical output value is changed from [-255; 255] to [0; 510]. Then all gray values are divided by two so that the output value is within the [0; 255] range. This guarantees that all pixels for which the gray values of both images are identical receive a medium gray value.
Since all examples presented in the following have been solved using this software and are therefore based on our particular solution pattern, we think it appropriate to outline this approach as a guideline before we proceed with the examples. g. regarding prescribed dimensions, serial numbers, presence of components etc. The complete task can frequently be subdivided into several independent parts, each checking a specific criterion. These individual checks typically run according to the following model: 1.
For example, images with a very large range of gray levels may suggest a logarithmic transformation. It is not necessary that f() can be expressed analytically. Practical implementations will often use a look-up table to speed up execution, allowing for completely arbitrary transformations (see Sect. 1). 1 Look-Up Tables We will start this section on gray scale transformations with a discussion of lookup tables since they can be used as a tool for all transformations described in the following.