Fourier Analysis of ‘in vivo’ Microscopic Images of Rat Prostate Tissue through Statistical Approach

Abstract

Fourier transform plays an important role in the field of medical image processing. The 2D Fourier Transform is an important method in image processing to decompose any 2D signal or image into its sine and cosine components. The output of the transformation represents the image in the frequency domain for the given input image in the spatial domain. This paper analyzes the brightness of prostate tissue using Fourier spectrum by the Fourier transform, histogram plot and statistical data in term of Mean, Median, Standard Deviation and maximum frequency of pixel values of the images. We have in vivo prostate tissue of rat after the taining, a technique used in microscopy to enhance contrast in the microscopic image. After analysis mainly in term of the Fourier spectrum and standard deviation, the comparative results of the images of prostate tissue based on the numerical values of statistical data are produced. The approach compares between prostate images to judge which image is having more brightness.