<![CDATA[Frequency response analysis is widely applied in digital image processing because of its ability to identify important features and information in images. In digital image processing, the Fourier transform is very useful for performing various types of operations such as image compression. Image compression is the process of reducing the size of a digital image without compromising important information. The Discrete Fourier Transform can assist in digital imagecompression because of its ability to analyze frequency response efficiently and accurately. The main objective of the Fourier transform is to transform images from the spatial domain (pixels) to the frequency domain so that we can analyze the frequency components contained in the image. In this study, we examined the frequency domain representation of a grayscale image measuring 128x128 pixels, using the Discrete Fourier Transform (DFT) method.Then, we also explore how image size and pattern affect the frequency domain representation. The DFT method was chosen to analyze the frequency response of digital images because of its ability to represent digital images in the frequency domain and DFT has a simple implementation which only requires basic mathematical operations, such as complex addition and multiplication. DFT is a very useful and effective technique in digital image processing. In the context of this study, researchers will analyze the impact of image compression on the frequency response of digital images obtained through the DFT method. Therefore the researcher intends to analyze the frequency response of the image, especially in the image magnitude part]]>
