TAILIEUCHUNG - Biosignal and Biomedical Image Processing MATLAB-Based Applications phần 10

Tham khảo tài liệu 'biosignal and biomedical image processing matlab-based applications phần 10', công nghệ thông tin, kỹ thuật lập trình phục vụ nhu cầu học tập, nghiên cứu và làm việc hiệu quả | 344 Chapter 12 both upper and lower boundaries an operation termed slicing since it isolates a specific range of pixels. Slicing can be generalized to include a number of different upper and lower boundaries each encoded into a different number. An example of multiple slicing was presented in Chapter 10 using the MATLAB gray2siice routine. Finally when RGB color or pseudocolor images are involved thresholding can be applied to each color plane separately. The resulting image could be either a thresholded RGB image or a single image composed of a logical combination AND or OR of the three image planes after thresholding. An example of this approach is seen in the problems. A technique that can aid in all image analysis but is particularly useful in pixel-based methods is intensity remapping. In this global procedure the pixel values are rescaled so as to extend over different maximum and minimum values. Usually the rescaling is linear so each point is adjusted proportionally with a possible offset. MATLAB supports rescaling with the routine imadjust described below which also provides a few common nonlinear rescaling options. Of course any rescaling operation is possible using MATLAB code if the intensity images are of class double or the image arithmetic routines described in Chapter 10 are used. Threshold Level Adjustment A major concern in these pixel-based methods is setting the threshold or slicing level s appropriately. Usually these levels are set by the program although in some situations they can be set interactively by the user. Finding an appropriate threshold level can be aided by a plot of pixel intensity distribution over the whole image regardless of whether you adjust the pixel level interactively or automatically. Such a plot is termed the intensity histogram and is supported by the MATLAB routine imhist detailed below. Figure shows an x-ray image of the spine image with its associated density histogram. Figure also shows the binary image

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