Image Processing: The Fourier Analysis

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Introduction

The Fourier analysis is responsible for relaying the two component frequencies magnitude which are the prime information carriers. Is also gives information about the frequency of each component. They are therefore crucial in processing of images and filtering since they assist one in evaluating signal behavior and eliminating other frequencies that are less important. This facilitates the acquisition of the desired results and enhancement of the image. (Leonid, 2004). The value and use of digital filtering in the realm of processing digital images cannot be compared to Fourier analysis due to its elementary position in this field.

When transform data for an 1D Fourier is obtained, the component DC is normally taking the first position of the index in the transform then the subsequent frequency bin in the spectrum is placed next. The same case applies to the 2D. Due to the Fourier transform, several frequency features take their positions in the four ends of the frequency spectrum. However, the outcome is rated to have an accuracy of100%, the visibility and improved frequency analysis can be advanced by changing the frequencies of the images from their initial positions at the corners to the center of the spectrum (Junichiro, 2009).

Surf and Mesh Plots

The purpose of mesh and surf plots is to make analysis and take a visual look of two-dimensional data in three dimensions. They produce parametric surface of three dimensions input data as explained below.

Function (Z)

With respect to function Z, the plot height appearing in the third dimension, or the z dimension represents the magnitude or value of the Z matrix elements at x-y index of the matrix or the position where we have the x-y coordinate. On the other hand, there can be a specification of the matrixes of x and y to obtain a representation of the plot in y and x suitable range expressed in scaling marks and lengths. The color of the map is another quality that can be exposed to control mechanisms to show the 3D plot, in which the matrix z height data is in direct proportion to the color of the map selected and then represented by the color of the 3D plot. (Mark, 2008).

The highest value in Z matrix plotted in a direct manner to the first color map’s color while the lowest is mapped to the color map’s and indicates last color. The rest of the values are distributed in a linear way. In addition, the functions support another quality which is the system of representing contours positioned below the 3D plots. The two functions work on identical input types in addition to possessing virtually same functions. The sole difference existing between the mess and surf plots is that wireframe parametric Z values represent the mesh plot while there is an empty area between the wire frames. The implication is that mesh plot is made up of color filled quadrilaterals also referred to as faceted shading.

Conclusion

Therefore, the function of Fourier transform is to assist us in observing and analyzing various frequency parts that guide us in determination of the impact and contribution of various components of the frequency in the images. In addition, this study has provided insights on realizing the procedures of performing various operations in the Fourier domain and the effects brought about by the image after its processing. The display of 2D matrix in the three-dimensional plot by use of surf and mesh plots has also been discussed. It is very important to understand the role of visualization in 3D and 2D since this assist in observing the Fourier spectrum of the image and how the various designed filters behave. Therefore, the application of the low pass filter produces a blurring impact in the generated image (Gaussian, 2008).

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