Image resolution enhancement using improved edge directed interpolation algorithm

Image resolution enhancement is a process to convert the low-resolution (LR) image into a high-resolution (HR) image. This method is applied in many image processing field. One of the commonly used techniques for image resolution enhancement is interpolation. The results of pixel interpolation can v...

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Bibliographic Details
Main Authors: Hossain, Md Shamim, Jalab, Hamid A., Kahtan, Hasan, Azma, Abdullah
Format: Conference or Workshop Item
Language:English
English
Published: Institute of Electrical and Electronics Engineers Inc. 2019
Subjects:
Online Access:http://umpir.ump.edu.my/id/eprint/37532/1/Image%20resolution%20enhancement%20using%20improved%20edge%20directed%20interpolation%20algorithm.pdf
http://umpir.ump.edu.my/id/eprint/37532/2/Image%20resolution%20enhancement%20using%20improved%20edge%20directed%20interpolation%20algorithm_ABS.pdf
http://umpir.ump.edu.my/id/eprint/37532/
https://doi.org/10.1109/ICCSCE47578.2019.9068535
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Institution: Universiti Malaysia Pahang
Language: English
English
Description
Summary:Image resolution enhancement is a process to convert the low-resolution (LR) image into a high-resolution (HR) image. This method is applied in many image processing field. One of the commonly used techniques for image resolution enhancement is interpolation. The results of pixel interpolation can vary significantly depending on the interpolation algorithm. Moreover, the conventional interpolation methods are not efficient to assign accurate interpolation value to the HR edge pixels. Therefore, in this study, we propose an improved edge directed interpolation (EDI) algorithm, which is able to preserve the sharpness of edges. The proposed method is divided into three main steps: edge pixel filtering; bi-cubic interpolation, and EDI. The edge pixels and non-edge pixels are separated by the adaptive edge filtering method. After that bi-cubic interpolation is applied for non-edge pixels. The Lagrange interpolation polynomial is used for bi-cubic interpolation. Finally, an improved EDI is applied to the edge pixels. The proposed method is tested on the several standard grayscale images and compared with the existing methods. According to the evaluation results, the proposed method provides the higher performance of the subjective and objective quality than the standing EDI methods.