Kompresi Citra Medis dengan DWT dan Variable Length Code
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https://doi.org/10.24843/MITE.2021.v20i02.P02
Abstrak
Paper ini merancang sebuah skema kompresi citra medis menggunakan DWT dengan mother wavelet Coiflet dan Symlet. Proses thresholding dan kuantisasi menjadi kunci terjadinya lossy compression di skema ini, dan data outputnya akan dikodekan dengan pengkodean Huffman atau Arithmetic. Terdapat empat kombinasi codec berbeda yakni: Coiflet-Huffman, Coiflet-Arithmetic, Symlet-Huffman yang masing-masing akan dianalisa kinerja kompresinya berdasarkan PSNR dan rasio kompresi. Pengujian kompresi menggunakan 3 citra medis grayscale berdimensi 160x160 piksel. Hasil pengujian menunjukan codec yang mampu menghasilkan PSNR dan rate paling optimal adalah codec Symlet-Arithmetic dengan nilai threshold yang dianjurkan yakni kurang dari 12. Pemberian nilai threshold diatas 12 akan menyebabkan PSNR citra rekonstruksi berada dibawah standar nilai minimum PSNR citra digital sebesar 30 dB.
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Referensi
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[13] A. Dixit, S. Majumdar, “Comparative Analysis Of Coiflet And Daubechies Wavelets Using Global Threshold For Image De-Noising”, International Journal of Advances in Engineering & Technology, vol. 6 no 5, pp. 2247-2252, Nov. 2013
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[15] R. C. Gonzalez, R. E. Woods, Digital Image Processingm (3rd Edition). New Jersey, United States: Prentice Hall. 2006
[16] G. Strang and T. Nguyen, Wavelets and Filter Banks. Cambridge Press, 1996
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[18] C. S. Burrus, R. A. Gopinath, and H. Guo. Introduction to Wavelets and Wavelet Transforms, New Jersey, United State: Prentice Hall, 1998
[19] L. L. Winger, A. N. Venetsanopoulos, “Biorthogonal modified coiflet filters for image compression”, Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing, May. 1998
[20] C. S. Burrus, I. E. Odegard, “Coiflet systems and zero moments”, IEEE Transactions on Signal Processing, vol. 46 no. 3, pp. 761-766, Mar. 1998
[21] K. Gopi, T.R. Shri, “Medical Image Compression Using Wavelet,” IOSR Journal of VLSI and Signal Processing (IOSR-JVSP), vol. 2 no. 4, pp 01-06, May-Jun. 2013
[22] I. Daubechies, “Orthonormal Bases of Compactly Supported Wavelet”, Communication on Pure and Applied Mathematics, vol. 41 no. 7, pp. 909-996, Oct. 1998
[23] A. Moffat. “Huffman Coding”, ACM Computing Surveys, vol. 1 no. 1, Jun. 2019
[24] D. A. Huffman, “A Method for the Construction of Minimum-Redundancy Codes”, Proceedings of the IRE, vol. 40 no. 9, pp. 1098-1101, Sept. 1952
[25] I.H. Witten, R. M. Neal, J. G. Cleary, “Arithmetic Coding for Data Compression”, Communication of the ACM, vol. 30 no. 6, pp 520-540, Jun. 1987
[26] G. G. Langdon, “An Introduction to Arithmetic Coding”, IBM Journal of Research and Development, vol. 28 no. 2, pp. 135-149, Mar. 1984
[27] R.H. Sianipar, H.S. Mangiri, I.K. Wiryajati. MATLAB Untuk Pemrosesan Citra Digital. Bandung, Indonesia: INFORMATIKA Bandung. 2013
[28] I. M. O. Widyantara, I. G. A. G. D. Putri, N. P. Sastra, N. M. A. E. D. Wirastuti, “Selection of Mother Wavelet for Medical Image Compression”, International Conference Smart Green Technology in Electrical and Information System, pp 171-177, Okt. 2016
[2] Sutoyo, T., Mulyanto, E., Suhartono, V., Nurhayati, O. D. & Wijanarto (2009). Teori pengolahan citra digital. Andi: Yogyakarta.
[3] A. M. Faza, C. Slamet, D. Nursantika, “Analisis Kinerja Kompresi Citra Digital dengan Komparasi DWT, DCT dan Hybrid (DWT-DCT)”, Jurnal Online Informatika, vol. 1 no. 1, pp. 1-5, Jun. 2016
[4] H. Amri, A. Khalfallah, M. Gargouri, N. Nebhani, J.C. Lapayre, M.S. Bouhlel, “Medical Image Compression Approach Based on Image Resizing, Digital Watermarking and Lossless Compression”, Journal of Signal Processing Systems, vol. 87, pp. 203-2014, Jul. 2017
[5] H. Sunil, Sharanabasaweshwar, G. Hiremath, “A combined scheme of pixel and block level splitting for medical image compression and reconstruction”, Alexandria Engineering Journal, vol. 57, pp. 767-772, Jun. 2018
[6] S. UmaMaheswari, V. V. SrinivasaRaghavan, “Lossless medical image compression algorithm using tetrolet transformation”, Journal of Ambient Intelligence and Humanized Computing, Feb. 2020
[7] S. Mallat, “Zero-Crossing of a Wavelet Transform”, IEEE Transactions on Information Theory, vol. 37 no. 4, pp. 1019-1033, Jul. 1991
[8] S. G. Mallat, “Multifrequency channel decompositions of images and wavelet models”, IEEE Transactions on Acoustics, Speech, and Signal Processing, vol. 37 no 12, pp. 2091-2110, Dec. 1989
[9] T. I. Saputra, Fauziah, N. Hayati, “Implementasi Discrete Wavelet Transform Pada Aplikasi Kompresi Citra Medis”, Jurnal Infomedia, vol. 4 no. 2, pp. 101-107, Dec. 2019.
[10] I. M. A. D. S. Atmaja, “Kompresi Citra Medis Menggunakan Packet Wavelet Transform dan Run Length Encoding”, Jurnal Matrix, vol. 8 no. pp 10-15, Mar. 2018
[11] I. D. G. H. Rastama, I. M. O. Widyantara, Linawati, “Teknik Kompresi Citra Medis dengan Transformasi Diskrit Wavelet dan Pengkodean Entropy”, Jurnal Rekayasa Sistem dan Teknologi Informasi, vol. 4 no. 1, pp. 155-162, Feb. 2020
[12] F. A. Wara, A. J. Santoso, B. Y. Dwiandiyanta, “Pengaruh Derau (Noise) pada Pemampatan Intra-Frame Urutan Citra Gerak tari Hegong Menggunakan Alihragam Gelombang Singkat”, Seminar Nasional Sains dan Teknologi, Nov. 2016
[13] A. Dixit, S. Majumdar, “Comparative Analysis Of Coiflet And Daubechies Wavelets Using Global Threshold For Image De-Noising”, International Journal of Advances in Engineering & Technology, vol. 6 no 5, pp. 2247-2252, Nov. 2013
[14] E. G. T. Swee, S. Elangovan, “Applications of symlets for denoising and load forecasting”, Proceedings of the IEEE Signal Processing Workshop on Higher-Order Statistics, Jun. 1999
[15] R. C. Gonzalez, R. E. Woods, Digital Image Processingm (3rd Edition). New Jersey, United States: Prentice Hall. 2006
[16] G. Strang and T. Nguyen, Wavelets and Filter Banks. Cambridge Press, 1996
[17] F. Liu, M. H. Cabronero, V. Sanchez, M. W. Marcellin, A. Bilgin, “The Current Role of Image Compression Standards in Medical Imaging”, Information, vol. 8 no. 131, Oct. 2017
[18] C. S. Burrus, R. A. Gopinath, and H. Guo. Introduction to Wavelets and Wavelet Transforms, New Jersey, United State: Prentice Hall, 1998
[19] L. L. Winger, A. N. Venetsanopoulos, “Biorthogonal modified coiflet filters for image compression”, Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing, May. 1998
[20] C. S. Burrus, I. E. Odegard, “Coiflet systems and zero moments”, IEEE Transactions on Signal Processing, vol. 46 no. 3, pp. 761-766, Mar. 1998
[21] K. Gopi, T.R. Shri, “Medical Image Compression Using Wavelet,” IOSR Journal of VLSI and Signal Processing (IOSR-JVSP), vol. 2 no. 4, pp 01-06, May-Jun. 2013
[22] I. Daubechies, “Orthonormal Bases of Compactly Supported Wavelet”, Communication on Pure and Applied Mathematics, vol. 41 no. 7, pp. 909-996, Oct. 1998
[23] A. Moffat. “Huffman Coding”, ACM Computing Surveys, vol. 1 no. 1, Jun. 2019
[24] D. A. Huffman, “A Method for the Construction of Minimum-Redundancy Codes”, Proceedings of the IRE, vol. 40 no. 9, pp. 1098-1101, Sept. 1952
[25] I.H. Witten, R. M. Neal, J. G. Cleary, “Arithmetic Coding for Data Compression”, Communication of the ACM, vol. 30 no. 6, pp 520-540, Jun. 1987
[26] G. G. Langdon, “An Introduction to Arithmetic Coding”, IBM Journal of Research and Development, vol. 28 no. 2, pp. 135-149, Mar. 1984
[27] R.H. Sianipar, H.S. Mangiri, I.K. Wiryajati. MATLAB Untuk Pemrosesan Citra Digital. Bandung, Indonesia: INFORMATIKA Bandung. 2013
[28] I. M. O. Widyantara, I. G. A. G. D. Putri, N. P. Sastra, N. M. A. E. D. Wirastuti, “Selection of Mother Wavelet for Medical Image Compression”, International Conference Smart Green Technology in Electrical and Information System, pp 171-177, Okt. 2016
Diterbitkan
2021-12-25
##submission.howToCite##
GARNITA DARMA PUTRI, I Gusti Ayu et al.
Kompresi Citra Medis dengan DWT dan Variable Length Code.
Jurnal Teknologi Elektro, [S.l.], v. 20, n. 2, p. 187-194, dec. 2021.
ISSN 2503-2372.
Tersedia pada: <https://ojs.unud.ac.id/index.php/mite/article/view/71408>. Tanggal Akses: 16 oct. 2025
doi: https://doi.org/10.24843/MITE.2021.v20i02.P02.
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