Using A Simple Linear Regression Function to Segmentation Image of the Hamrin Marshes for the Years (2020/2021 – 2021/2022)

Abstract

Simple linear regression analysis is a statistical technique with an understandable mathematical formula that is used to study the relationship between a dependent and an explanatory variable. The regression equation is also used to predict the value of the dependent variable at a specific value of the independent variable. Therefore, it is a statistical function that interprets a certain phenomenon through its results. In this research, it was suggested to employ the simple linear regression function in image processing, and it gave satisfactory results in this field. Where the simple linear regression function was used to slice the digital images using the local thresholding technique, by taking the vector of the simple linear regression function and considering it as the threshold limit for segmenting the images. It produced sliced images containing the most significant areas of interest, with the removal of unnecessary or significant areas. And it demonstrated its effectiveness in extracting all the features of the images. This technique was applied to satellite images of the Hamrin Marsh in Diyala taken during two years that were exposed to drought. The simple linear regression function was estimated from the images to be the segmentation threshold, and it was found that the first image of the Hamrin Marsh before the drought had more features than the image after the drought, in which most of the features had vanished.