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Technique in carrying out data compression is an important point in technological developments. With compression in data in the form of text can include many uses, including for data transfer, copying and for backing up data. From its uses, this aspect is important for data security. There are many compression techniques on the data, including using huffman algorithms and unary code. One of its applications will be implemented on a text data that is widely used by digital actors in storing important data. The data must not be known by unauthorized parties in accessing the data. Therefore, huffman algorithms and unary code can solve this problem. By compressing the selected data also encrypts it as an extra security. The Huffman algorithm is a lossless compression algorithm or a technique that does not change the original data, by converting the unit of data content into bits. So this algorithm is widely used in the compression process. The Unary Codes algorithm is also a lossless compression technique that is generally used by combining several modification techniques. In this unary codes algorithm, each symbol in the string will be searched for its frequency. Then sorted from the last order (descending). The use of these two text data compression techniques results in a file size that is smaller than the original but can be returned to the original data, Teknik dalam melakukan kompresi data merupakan suatu poin penting dalam perkembangan teknologi. Dengan kompresi dalam data berupa teks dapat mencakup banyak kegunaan, diantaranya untuk transfer data, melakukan penyalinan maupun untuk mencadangkan data. Dari kegunaan-kegunaannya tersebut aspek ini penting untuk keamanan data. Sangat banyak teknik kompresi pada data, diantaranya adalah dengan menggunakan algoritma huffman dan unary code. Salah satu penerapannya akan diimplementasikan pada suatu data teks yang banyak digunakan oleh pelaku digital dalam menyimpan data penting. Data tersebut tidak boleh diketahui oleh pihak yang tidak berwenang dalam mengakses data tersebut. Maka dari itu algoritma huffman dan unary code dapat memecahkan permasalahan tersebut. Dengan melakukan kompresi pada data yang dipilih juga mengenkripsinya sebagai pengamanan ekstra. Algoritma Huffman merupakan algoritma kompresi lossless atau teknik yang tidak mengubah data aslinya, dengan cara mengubah satuan isi data menjadi bentuk bit. Sehingga algoritma ini banyak dipakai dalam proses kompresi. Algotitma Unary Codes juga merupakan teknik kompresi lossless yang umumnya digunakan dengan menggabungkan beberapa teknik modifikasi. Dalam algoritma unary codes ini setiap simbol pada string akan akan dicari frekuensinya. Kemudian diurutkan dari urutan paling akhir (descending). Penggunaan dua teknik kompresi data teks ini menghasilkan ukuran file yang lebih kecil dari aslinya namun dapat dikembalikan lagi menjadi data asli tersebut.

The Vernam-cipher is known as a one-time pad of algorithm that is an unbreakable algorithm because it uses a typically random key equal to the length of data to be coded, and a component of the text is encrypted with an element of the encryption key. In this paper, we propose a novel technique to overcome the obstacles that hinder the use of the Vernam algorithm. First, the Vernam and advance encryption standard AES algorithms are used to encrypt the data as well as to hide the encryption key; Second, a password is placed on the file because of the use of the AES algorithm; thus, the protection record becomes very high. The Huffman algorithm is then used for data compression to reduce the size of the output file. A set of files are encrypted and decrypted using our methodology. The experiments demonstrate the flexibility of our method, and it’s successful without losing any information.

RESUMEN: Estudio de las diferentes técnicas de compresión, implementación de un codificador de video basado en el estándar H.261 de la ITU-T. Y, el posterior análisis de cada uno de los módulos que lo integran. ABSTRACT: Study of the different compression techniques, implementation of a video encoder based on the H.261 standard of the ITU-T. And, the subsequent analysis of each one of the modules that make it up. Grado en Ingeniería de Tecnologías de Telecomunicación

Huffman is one of the compression algorithms. It is the most famous algorithm to compress text. There are four phases in the Huffman algorithm to compress text. The first is to group the characters. The second is to build the Huffman tree. The third is the encoding, and the last one is the construction of coded bits. The Huffman algorithm principle is the character that often appears on encoding with a series of short bits and characters that rarely appeared in bit-encoding with a longer series. Huffman compression technique can provide savings of 30% from the original bits. It works based on the frequency of characters. The more the similar character reached, the higher the compression rate gained.

The paper is about the transmission, compression, detection of the video based on simulation for the various communication applications. The video and image compression overcomes the problem of reducing the amount of data required to the information that has to be transmitted and this saves the bandwidth required for transmission of data and memory which is required for storage purpose. Hence video compression reduces the volume of the video data with a small change in quality of the video. Compressed video transmission can be done over a channel by huffman coding for the source at transmitter side and then channel codes is done by technique called hamming. The data which is to be sent through channel is a BPSK modulated so the received data is demodulated followed by the channel decoding, source decoding using inverse of the techniques used in the transmitter side to obtain the original transmitted video. The above procedure is done for the input video taken by camera and this compressed video can be transmitted then detected at receiver by digital communication system(DCS) which is simulated in the MATLAB.

RESUMEN: En este trabajo se va a realizar el estudio de un codificador de video basado en el estándar H.261. Se llevará a cabo un análisis de cada uno de los módulos necesarios para su implementación. Se realizará un código software en C/C++ de los algoritmos y se obtendrá un resultado a evaluar. ABSTRACT: For this work, a video encoder based on the H.261 standard will be studied. To do this, an analysis of each modules is necessary for its implementation. A software code will be made in C / C ++ of the algorithms and a result to be evaluated will be obtained. Grado en Ingeniería de Tecnologías de Telecomunicación

Compression can be used to reduce the size of files and speeding up the transmission time over networks. However, not all compression techniques have the same features and capabilities to improve the performance of transmission over networks. This paper shows a comparison between different compression algorithms in order to improve the performance of web-services over the Internet. Nowadays, Service Oriented Architecture (SOA) being used heavily between applications as interaction between loosely coupled services, which are function independently. Therefore, fast and efficient services offered through the web services are needed. Enhancing performance of web services, would improve overall system's performance. As a result, compressing and reducing the size of SOAP messages traveling over the network, improves the webs-service performance. This paper compares the performance of web-services by compressing SOAP messages using Tagged Sub-optimal Code (TSC) and Huffman Encoding Algorithms. Experimental results show that web-services compressed using TSC speeds up the performance of web-services compared to normal web-services and web-services compressed using Huffman encoding.

In image compression, we can reduce the quantity of pixels used in image representation without excessively change image Visualization. Reducing image size enhance images sharing, transmitting and storing. This paper examines the performance of a set of lossless data compression algorithms which are RLE, Delta encoding and Huffman techniques on binary image, grey level images and RGB images.

Penelitian ini bertujuan untuk mengkompresi citra dengan menggabungkan metode DCT dan Algoritma Huffman untuk membuat kapasitas file gambar menjadi kecil sehingga dapat menghemat media penyimpanan dan tidak lambat jika pengiriman citra dari satu tempat ke tempat lain. Discrete Cosine Transform (DCT) adalah sebuah teknik yang mengubah sinyal ke dalam komponen frekwensi dasar dan Algoritma Huffman adalah algoritma yang digunakan untuk membuat kompresi jenis lossy compression yaitu penempatan data dimana tidak ada satu byte pun data yang hilang sehingga data tersebut utuh dan disimpan sesuai dengan aslinya. Dengan menggabungkan metode Discrete Cosine Transform (DCT) dan Algoritma Huffman dapat mengkompresi gambar dengan maksimal. Dengan teknik lossy compression pada DCT, kompresi citra yang dihasilkan sedikit mengurangi warna ( pixel ) namun tampak tidak terlihat perbedaannya dengancitra asli sebelum dikompresi. Hasil kompresi tergantung pada pemilihan kualitas kompresi yang diinginkan. Jika memilih kompresi dengan kualitas standar, maka citra hasil kompresi dengan citra yang asli tidak akan terlihat perbedaannya namun pengurangan ukuran bytes tidak terlalu drastis. Tetapi apabila kita memilih kualitas kompresi rendah, maka ukuran bytes pada citra akan berkurang namun kualitas gambar hasil kompresi akan terlihat perbedaannya dengan citra asli.

Desde la segunda mitad del siglo XX una nueva generación de historiadores empezó a revisar las fuentes relacionadas con el pensamiento griego, en particular el pitagorismo, rescatando el pensamiento y obra de un conjunto de autores, tradicionalmente minimizados en la historiografía filosófica tradicional. En la primera parte se plantean algunos problemas generales asociados con la historiografía pitagórica, mientras que en la segunda se presenta el caso de Arquitas de Tarento (435-440/360-350 a.C.)

Peer-reviewed Artículos técnicos con código fuente para ilustrar esencialmente el funcionamiento y las ideas que hacer funcionar los sistemas de compresión basados en estadística (Huffman) y combinatoria (Lempev-Ziv) sin entrar en detalles divulgativos, sólo tecnológicos. Articles tècnics amb codi font per il.lustrar essencialment el funcionament i les idees per fer funcionar els sistemes de compressió basats en estadística (Huffman) i combinatòria (Lempev-Ziv) sense entrar en detalls divulgatius, només tecnològics. Whitepaper with source code to illustrate the functionality and the ideas which make work the compression systems based on statistic (Huffman) and combinatory (Lempev-Ziv) without going into informative details, just technological.

Tez (Yüksek Lisans) -- İstanbul Teknik Üniversitesi, Fen Bilimleri Enstitüsü, 2002, Thesis (M.Sc.) -- İstanbul Technical University, Institute of Science and Technology, 2002, Bu çalışmada dalgacık dönüşümü kullanılarak biyomedikal görüntülerin sıkıştırılması incelenmiştir. İlk olarak entropi ve oran bozulma gibi görüntü sıkıştırmaya uygulanan kaynak kodlama teorisinin temel kavramlarına değinildi. Bunu Huffman, aritmetik, koşan uzunluk, dönüşüm ve altband gibi kayıplı ve kayıpsız kodlama teknikleri izledi. Fraktal kodlama kavramına da kısaca değinildi. Daha sonra JPEG görüntü sıkıştırma standardı kısaca açıklandı. Sonra görüntü kodlama uygulamaları açısından dalgacık teorisi açıklandı. Dalgacıkların durağan olmayan işaret analizindeki faydaları tartışıldı. Dalgacık ve çoklu çözünürlük analizi arasındaki bağıntılar gösterildi. Sonra dalgacıkların düzenlilik ve kaybolma momenti özelliklerine tartışıldı. Sonra bir boyutlu dalgacık dönüşümü iki boyutlu duruma genişletildi. Buradan dalgacık tabanlı bir kodlayıcı tasarlandı. Örnek medikal görüntüler dalgacık kodlayıcısında sıkıştırıldı ve JPEG sonuçlarıyla karşılaştırıldı., In this study biomedical image compression was investigated using wavelet transform. The fundamental concepts of source coding theory, namely entropy and rate-distortion, were reviewed as applied to image compression. This was followed by a review of lossless and lossy compression techniques, such as Huffman, arithmetic, run-length, transform and subband coding. The concept of fractal coding was also introduced briefly. The wavelet theory from the perspective of image coding application was reviewed. The usefulness of between wavelets and multiresolution analysis was then established. The regularity and vanishing moments properties of wavelets were discussed. 1-D wavelet transform was then extended to 2-D case. Hence a wavelet based coder was designed. Sample biomedical images were compressed by the wavelet coder and compared with results of JPEG., Yüksek Lisans, M.Sc.