![]() ![]() The simple examples show the methods steps and additional features ( Figure 5). This chapter aims to serve as guiding overview for the entropy consideration as a processing method. The results of the commands are the plots and figures presented within the text. The description is completed by mathematical equations as well as by commented MATLAB commands. Three different methods for using the entropy in image processing are introduced, entropy filtration, entropy segmentation, and point information gain. The lecture opens the intensity histogram function, and the induction continues through the statistical parameters, like central moments, to the information entropy. In this chapter, the question of image processing is discussed. Thus, the amount of bins is usually given by the amount of quantization levels during the sampling process ( Figures 3 and 4). However, in the digital era, we are live with the datasets, which are discrete representation of discrete events of the real signal. The estimation of proper histogram, as a representation of the probability distribution function, suffers with the question of the proper binning. One of the most useful plots in the signal or image analysis is the signal histogram, an expression of signal abundance, first introduced by Pearson. Is the interpretation of the processed data.Ĭonsists of comparison, classification, clustering, decomposition, pattern recognition, identification, and so on. ![]() Includes tasks as calibration, filtering, feature detection, alignment, normalization, modeling, and so on. Transforms the raw data into more transparent format for the analysis. Is the necessary step before the analysis. Recently, Katajama pronounced a clear distinction between the processing and analysis ( Figures 1 and 2). Their origin is different from statistics, physics, artificial intelligence, or systems theory. These methods are belonging to the large group of data processing and analysis. The real signals have to be evaluated with numerous methods for filtration, transformation, alignment, comparison, and so on to extract the hidden knowledge. MATLAB and its toolboxes are trademarks or registered trademarks of The MathWorks, Inc. MATLAB environment enables advanced data processing and analysis, especially using its toolboxes like signal processing, image processing, and statistics. ![]()
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