Implementasi Metode Line Column Interpolation Untuk Pembesaran Skala Citra Hasil Cropping Selection Area

 (*)James Supriadi S Lase Mail (Universitas Budi Darma, Medan, Indonesia)

(*) Corresponding Author

Submitted: August 14, 2021; Published: September 30, 2021

Abstract

Image processing is any form of signal processing where the input is an image, such as a photo or video frame, while the output of image processing can be an image or a number of characteristics or parameters associated with the image. A digital image is a sequence of real or complex numbers represented by certain bits. Generally, digital images form rectangles or squares (in some imaging systems there are also hexagons) that have a certain width and height. At the time of sending the image, it often experiences damage to the image which results in a decrease in quality or a decrease in image quality. Often the information presented with the image is different from the original image. In this study, the authors propose the Line-Column Interpolation Method (LCI) as a new method. This method was tested to enlarge the size of medical images. Larger image sizes produce larger objects while preserving their local structure values. Thus, the results of the enlargement make better observations of objects in the image. The benefits that the author wants to achieve in this study are to be able to obtain better image scale enlargement results than before and to find out the advantages and disadvantages of using the LineColoumn Interpolation method in image scale enlargement.

Keywords


Quality Improvement; Line-Column

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This work is licensed under a Creative Commons Attribution 4.0 International License.