Role of Mathematics in Digital Image Processing

Author(s): Dr. S Sivagami, Saranya C, Sailaja Mulakaluri, Annie Christilla, Kalpana R, and Ashtalakshmi K

Abstract:

Numerous fundamental image processing tasks, such as edge detection, segmentation, enhancement, de-noising, and de-blurring, are closely linked to mathematics. Studying these kinds of image processing jobs offers a special chance to use mathematical methods and tools to a number of image processing applications in different scientific domains. A variety of mathematical techniques are employed, such as the Fourier transform, low-pass and high-pass filters, zerocrossings of the Laplacian, and first- and second-order partial derivatives, the gradient, the Laplacian, and their discrete approximations by finite differences, averaging filters, order statistics filters, and convolution, for image filtering in the spatial domain and the frequency domain, respectively. Image restoration, image segmentation, image enhancement, de-noising, de-blurring, and other image processing activities are among the most often performed ones. Numerous fundamental image processing tasks, such as edge detection, segmentation, enhancement, de-noising, and de-blurring, are closely linked to mathematics. Studying these kinds of image processing jobs offers a special chance to use mathematical methods and tools to a number of image processing applications in different scientific domains.

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