A Note on Eigenvalues Significance in Digital Image Processing

Resumo

This paper discusses the importance of eigenvalues in the area of digital image processing (DIP). A digital image may be in the form of a matrix data. The properties of eigenvalues, in the case of standard matrices, have been discussed. We started by converting a standard color image a grayscale image to make it easier to understand how the image is represented in a matrix, and then applied the properties and theorems using the MATLAB software. We also give a comparative analysis of different image noise reduction methods that make use of the eigenvalues of the image data. To measure the quality of image compression using various filters, we used mean square error (MSE) and peak signal to noise ratio (PSNR). Mean square error (MSE) and PSNR have also been used to conduct the experiments and to further prove the validity of the proposed theories and methodologies.