IMPLEMENTASI KOMPRESI CITRA DIGITAL DENGAN MEMBANDINGKAN METODE LOSSY DAN LOSSLESS COMPRESSION MENGGUNAKAN MATLAB

IMPLEMENTASI KOMPRESI CITRA DIGITAL DENGAN MEMBANDINGKAN METODE LOSSY DAN LOSSLESS COMPRESSION MENGGUNAKAN MATLAB

• By Pangesti, witriana, endah; Widagdo, galih; Riana, Dwiza; Hadianti, Sri;
• Jurnal Nasional Terakreditasi
• 407
• 53-58

Current image processing technology has been developed, one of which is compression technology. Digital image compression is an attempt to transform data or symbols, without involving significant changes to digital images for humans who observe them. Image is another term for image as one of the multimedia components that plays a very important role as a form of visual information. Lossy compression and lossless compression where the lossy compression method is a data compression method that removes some of the information as a lossless compression method is a method of data compression with no data information being released or discarded through the compression process. Required after the decompression process the number of bits (bytes) of data or information in the overall data result is the same as the full data (Saragih and Harahap 2019). From previous studies, namely the Implementation of Digital Image Compression By finding Digital Image Quality (Raharja and Harsadi 2018) the authors proceed to use 20 different images compressed with lossless compression methods, given an average as compresses with forty percent percent. Previous research papers that use lossy methods produce an average of sixty percent compress and research papers that the authors do with lossless methods that produce an average compression of forty-nine percent, it can be concluded. 

• Katakunci Imagery, Lossy compression, Lossless compression, MATLAB, Compressing.
• URL https://ejournal.bsi.ac.id/ejurnal/index.php/khatulistiwa/article/view/7759
• Penerbit ,

REFERENSI

REFERENSI Rahmat, H., Damiri, D. J., & Susanto, A. (2012). Implementasi Kompresi Data Pada Jaringan Komputer Menggunakan Algoritma Zlib. Jurnal Algoritma, 9(1), 119–124. https://doi.org/10.33364/algoritma/v.9- 1.119 Saragih, N. E., & Harahap, F. (2019). Perancangan Aplikasi Kompresi SMS dengan Algoritma Dynamic Markov Compression pada Android. 7(2548–3528), 1–6. Hidayatullah, Muhammad Taufiq, Efri Suhartono, and Irma Safitri s t. 2019. “Kompresi Arithmetic Coding menggunakan teknik cs dan arithmetic compression coding using cs and combined technique of dct and svd method.” E-proceeding of engineering 6 (1): 503–10. Ikhsan, Muhammad. 2016. “Implementasi Kompresi Citra Digital” 1 (979-458–924): 258–66. Pandi, Nauli Simangunsong, Hery Sunandar, Metode Deflate, and Hery Sunandar. 2015. “Kompresi Citra Berwarna Menggunakan Metode Deflate” 10 (2301–9425): 1–5. Pardosi, Irpan Adiputra, and Ali Akbar Lubis. 2019. “Analisis Kualitas Citra Hasil Reduksi Noise Menggunakan Spatial Median Filter Dan Adaptive Fuzzy Filter Terhadap Variasi Kedalaman Citra.” Indonesian Journal of Information Systems 1 (2): 78. https://doi.org/10.24002/ijis.v1i2.1939. Raharja, Bayu Dwi, and Paulus Harsadi. 2018. “Implementasi Kompresi Citra Digital Dengan Mengatur Kualitas Citra Digital.” Jurnal Ilmiah SINUS 16 (2): 71–77. https://doi.org/10.30646/sinus.v16i2.363. Rozi, Apri, Nelly Astuti Hasibuan, and Imam Saputra. 2019. “PERBANDINGAN METODE HIGH-BOOST FILTERING DAN.” Jurnal Pelita Informatika 18 (2301–9425): 7–12. Saragih, Nidia Enjelita, and Fitriana Harahap. 2019. “Perancangan Aplikasi Kompresi SMS Dengan Algoritma Dynamic Markov Compression Pada Android” 7 (2548–3528): 1–6. Syahputra, Rahmad Eko, Deteksi Tepi, Metode Edge Linking, and Operator Sobel. 2019. “Dalam Citra Digital Dengan Metode.” Informatika, Jurnal Pelita 18 (2301–9425): 62–68. Wahyuni, Meri Sri. 2019. “Analisa membandingkan hasil kompresi file mpeg-4 dan flv menggunakan algoritma huffman dan lz77.” Saintek itm 32 (1): 40–47.