Time Optimization of Watermark Image Quality Using Run Length Encoding Compression

Adiyah Mahiruna(1*), Eko Hari Rachmawanto(2), Deden Istiawan(3)


(1) Institut Teknologi Statistika dan Bisnis Muhammadiyah Semarang, Semarang, Indonesia
(2) Universitas Dian Nuswantoro, Semarang, Indonesia
(3) Institut Teknologi Statistika dan Bisnis Muhammadiyah Semarang, Semarang, Indonesia
(*) Corresponding Author

Abstract


Internet technology continues to have a significant impact on digital media, such as text, images, audio, and video. One effect is the ease of exchange, distribution, and duplication of digital data; on the other hand, this ease raises the problem of digital data being protected by copyright or digital data confidentiality. Watermarking is a way to protect digital data rights. Extensive research on watermarking has been conducted, including a hybrid DWT-DCT-SVD approach. Several studies have found weaknesses in the message insertion process; for example, the time required to insert a watermark image is relatively long, particularly for large images. To address the problem of long message insertion times, this study applies a compression process to the original image before the watermark image insertion process. The original image to be inserted into the watermark image is compressed using the run-length encoding (RLE) algorithm. The results of RLE compression demonstrate that image file size is reduced significantly, which optimizes the watermarking process. The experimental results demonstrate that watermarked images with RLE compression preprocessing exhibit better imperceptibility and comparable or improved PSNR values. Specifically, the image "Elaine" showed a PSNR improvement from 28.7541 to 31.4502 with RLE compression. These findings demonstrate that combining DWT-DCT-SVD with RLE compression not only reduces watermarking time but also maintains or enhances image quality, providing a robust solution for digital copyright protection.

Keywords


Watermarking; Discrete wavelet transform; Discrete cosine transform; Singular Value Decomposition; Compression; Run Length Encoding

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References


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DOI: https://doi.org/10.26714/jichi.v4i2.12058

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Journal of Intelligent Computing and Health Informatics (JICHI)
ISSN 2715-6923 (print) | 2721-9186 (online)
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Faculty of Engineering
Universitas Muhammadiyah Semarang

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