Fundamentals of stack filters and their use in image processing
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Image processing is a field that has seen tremendous growth in the last few decades. After computers became common for commercial use in the late 1970s, digital image processing was recognized as an important electrical engineering discipline. Today, there are numerous applications of image processing, such as object recognition, compression, noise reduction, enhancement, etc. The earliest algorithms used in image processing involved linear systems and procedures. These systems have shown good results for certain application such as edge detection; however, linear methods are not robust enough to solve many image processing problems. Non linear algorithms provide much better results than linear filters in many applications because of their robustness to outliers. Due to the need for nonlinear filters, algorithms must be developed to choose appropriate filters that are optimized for the problem at hand. Thus, our goal is to find fast algorithms for designing optimal stack filters.