Improvement for Single Image Super-resolution and Image Segmentation by Graph Laplacian Regularizer based on Differences of Neighboring Pixels

Universitas Yudharta Pasuruan, Lukman Hakim (2022) Improvement for Single Image Super-resolution and Image Segmentation by Graph Laplacian Regularizer based on Differences of Neighboring Pixels. INASS The Intelligent Network and Systems Society, 15 (1). pp. 95-105.

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Abstract

The neighboring relationship of the pixels is fundamental information in the image. Utilizing neighboring pixel information provides an advantage over using only pixel-to-pixel information. This study presents a regularization term based on the differences of neighboring pixels. We define the differences of neighboring pixels by using the Graph Theory approach. We then propose an effective graph Laplacian regularization to enforce the differences between pixels as the nodes and differences between nodes as edges. In our scheme, Graph Laplacian constructs from the output of the convolutional neural network and ground-truth image. The generated differences matrices from the output and ground-truth are combined as a Laplacian regularization term used as the deep convolutional neural network's new objective function. Experiments show that our scheme successfully captures pixel neighbor relations and improves the performance of the convolutional neural network better than the baseline without a regularization term. Qualitative and quantitative results show that our developed regularizer proved to enhance the boundary structure on image super-resolution and image segmentation tasks, which is achieved Structural Similarity Index (SSIM) of 0.9604 and 0.8263 on Cartoon set and Manga109 datasets and area under the curve (AUC) of 0.9740 and 0.9561 on DRIVE and STARE datasets, respectively. Keywords: Graph laplacian regularization, Differences, Neighboring pixel, Boundary structure, Deep learning, Superresolution, Segmentation

Item Type:	Article
Contributors:	Contribution Contributors Email UNSPECIFIED Universitas Yudharta Pasuruan, Lukman Hakim UNSPECIFIED
Subjects:	Teknologi & Ilmu Terapan > Ilmu Teknik dan Ilmu yang Berkaitan
Divisions:	Fakultas Teknik > Teknik Informatika
Date Deposited:	25 Oct 2023 06:03
Last Modified:	25 Oct 2023 06:03
URI:	https://repository.yudharta.ac.id/id/eprint/3212

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