LCTD: A lossless compression tool of FASTQ file based on transformation of original file distribution

Analysis of DICOM Image Compression Alternative Using Huffman Coding

Journal of Healthcare Engineering ◽

10.1155/2019/5810540 ◽

2019 ◽

Vol 2019 ◽

pp. 1-11 ◽

Cited By ~ 2

Author(s):

Romi Fadillah Rahmat ◽

T. S. M. Andreas ◽

Fahmi Fahmi ◽

Muhammad Fermi Pasha ◽

Mohammed Yahya Alzahrani ◽

...

Keyword(s):

Medical Imaging ◽

Lossless Compression ◽

Huffman Coding ◽

Imaging Procedures ◽

Compression Method ◽

File Size ◽

Dicom Image ◽

Dicom File ◽

Original File

Compression, in general, aims to reduce file size, with or without decreasing data quality of the original file. Digital Imaging and Communication in Medicine (DICOM) is a medical imaging file standard used to store multiple information such as patient data, imaging procedures, and the image itself. With the rising usage of medical imaging in clinical diagnosis, there is a need for a fast and secure method to share large number of medical images between healthcare practitioners, and compression has always been an option. This work analyses the Huffman coding compression method, one of the lossless compression techniques, as an alternative method to compress a DICOM file in open PACS settings. The idea of the Huffman coding compression method is to provide codeword with less number of bits for the symbol that has a higher value of byte frequency distribution. Experiments using different type of DICOM images are conducted, and the analysis on the performances in terms of compression ratio and compression/decompression time, as well as security, is provided. The experimental results showed that the Huffman coding technique has the capability to compress the DICOM file up to 1 : 3.7010 ratio and up to 72.98% space savings.

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Perbandingan Algoritma Huffman Dan Run Length Encoding Untuk Kompresi File Audio

Talenta Conference Series Science and Technology (ST) ◽

10.32734/st.v1i1.183 ◽

2018 ◽

Vol 1 (1) ◽

pp. 010-015

Author(s):

Helbert Sinaga ◽

Poltak Sihombing ◽

Handrizal Handrizal

Keyword(s):

Compression Ratio ◽

Lossless Compression ◽

The Other ◽

Audio File ◽

Run Length ◽

Huffman Algorithm ◽

Three Stages ◽

Original File ◽

Audio Files ◽

Comparison Of The Results

Penelitian ini dilakukan untuk menganalisis perbandingan hasil kompresi dan dekompresi file audio*.mp3 dan *.wav. Kompresi dilakukan dengan mengurangi jumlah bit yang diperlukan untuk menyimpan atau mengirim file tersebut. Pada penelitian ini penulis menggunakan algoritma Huffman dan Run Length Encoding yang merupakan salah satu teknik kompresi yang bersifat lossless.Algoritma Huffman memiliki tiga tahapan untuk mengkompres data, yaitu pembentukan pohon, encoding dan decodingdan berkerja berdasarkan karakter per karakter. Sedangkan teknik run length ini bekerja berdasarkan sederetan karakter yang berurutan, yaitu hanya memindahkan pengulangan byte yang sama berturut-turut secara terus-menerus. Implementasi algoritma Huffman dan Run Length Encoding ini bertujuan untuk mengkompresi file audio *.mp3 dan *.wav sehingga ukuran file hasil kompresi lebih kecil dibandingkan file asli dimana parameter yang digunakan untuk mengukur kinerja algoritma ini adalah rasio kompresi, kompleksitas yang dihasilkan. Rasio kompresi file audio *.mp3 menggunakan Algoritma Huffman memiliki rata-rata 1.204% sedangkan RLE -94.44%, dan rasio kompresi file audio *.wav memiliki rata-rata 28.954 % sedangkan RLE -45.91%. This research was conducted to analyze the comparison of the results of compression and decompression of *.mp3 and *.wav audio files. Compression was completed by reducing the number of bits needed to save or send the file. In this study, the researcher used the Huffman algorithm and Run Length Encoding which is one of the lossless compression techniques. The Huffman algorithm has three stages to compress data, namely tree formation, encoding and decoding which work based on characters per character. On the other hand, the run length technique works based on a sequence of sequential characters that only move the repetitions of the same byte in succession continuously. The implementation of the Huffman algorithm and Run Length Encoding aimed to compress audio files *.mp3 and *.wav so that the size of the compressed file was smaller than the original file where the parameter used to measure the performance of this algorithm was the compression ratio, and the resulting complexity.*.Mp3 audio file compression ratio using Huffman Algorithm had an average of 1.204% while RLE -94.44%, and compression ratio *.wav audio files had an average of 28.954% while RLE -45.91%.

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