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"Data is of high importance especially for large companies. When data is abundant, some companies thus require a good software or an effective tool to compress the data. Data compression is the process of converting an input data stream into another data stream that has a smaller size. Data compression software is very useful because it can reduce the size of the data itself. The main idea of the LZW encoding is to identify the longest pattern for each accumulated segment of the source text, and encode them by the indices in the dictionary. If no match is found in the dictionary, the segment will become a new entry to the dictionary. There will be a match found in the dictionary if the same segment is seen next time. We put another check on the segment by adding a second index on a dictionary that represents a reversed sequence of characters. The experiment was conducted on text file with the size from about a 3,000 up to 60,000 Bytes and a code with length of bits from 9 to 16 bits. The results show that our proposed method gave fewer (better) compression ratio (16%, on average) compared to the standard LZW (56%) and LZW++ (36%)"

"penelitian ini diusulkan implementasi 2D dan 3D Set Partitioning In Hierarchical Trees (SPIHT) coding pada kompresi data ECG multi-lead. Implementasi SPIHT mereduksi tiga jenis redundansi yang umumnya terdapat pada sinyal electrocardiogram (ECG), yaitu redundansi intra-beat, inter-beat, dan inter-lead. Kami juga mengusulkan tiga teknik optimisasi untuk meningkatkan kinerja kompresi lebih lanjut dengan mengelompokkan sinyal ECG yang berasal dari beberapa lead, menyusun kembali posisi ECG cycle pada 2D ECG array (beat reordering), dan menormalisasikan amplitudo dari 2D ECG array dengan residual calculation. Beat reordering menyusun posisi beat pada 2D ECG array berdasarkan kemiripannya dengan beat terdekat. Penyusunan ini mengurangi variasi antar beat-beat yang berdekatan sehingga 2D ECG array mengandung lebih sedikit komponen frekuensi tinggi. Residual calculation mengoptimalkan penggunaan ruang penyimpanan lebih lanjut dengan meminimalkan variasi amplitudo dari 2D ECG array. Hasil eksperimen terhadap sejumlah record pada St Petersburg INCART 12-lead Arrhythmia Database menunjukkan bahwa metode yang diusulkan menghasilkan distorsi rendah pada rasio kompresi 8 dan 16. Hasil eksperimen juga memperlihatkan bahwa pendekatan 3D SPIHT memiliki kinerja kompresi yang lebih baik dibanding 2D SPIHT. Untuk mengevaluasi kualitas sinyal hasil rekonstruksi pada permasalahan klasifikasi, pada penelitian ini kinerja dari metode kompresi sinyal ECG dianalisis dengan cara membandingkan sinyal asli dengan sinyal hasil rekonstruksi pada dua permasalahan; pertama, klasifikasi sleep stage berdasarkan sinyal ECG; kedua, klasifikasi arrhythmia. Hasil eksperimen menunjukkan bahwa akurasi dari klasifikasi sleep stage dan klasifikasi arrhythmia menggunakan sinyal hasil rekonstruksi sebanding dengan menggunakan sinyal input. Metode yang diusulkan dapat mempertahankan karakteristik sinyal pada kedua permasalahan klasifikasi tersebut.

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In this study we proposed the implementation of 2D and 3D Set Partitioning In Hierarchical Trees (SPIHT) coding to a multi-lead ECG signal compression. The implementation of SPIHT coding decorrelates three types of redundancy that typically found on a multi-lead electrocardiogram (ECG) signal i.e. intra-beat, inter-beat, and inter-lead redundancies. We also proposed three optimization techniques to improve the compression performance further by grouping the ECG signal from precordial and limb leads, reordering the ECG cycles position in the 2D ECG array, and normalizing the amplitude of 2D ECG array by residual calculation. Beat reordering rearranged beat order in 2D ECG array based on the similarity between adjacent beats. This rearrangement reduces variances between adjacent beats so that the 2D ECG array contains less high frequency component. The residual calculation optimizes required storage usage further by minimizing amplitude variance of 2D ECG array.

Our experiments on selected records from St Petersburg INCART 12-lead Arrhythmia Database show that proposed method gives relatively low distortion at compression rate 8 and 16. The experimental results shows that 3D SPIHT approach gives better compression performance than 2D SPIHT. To evaluate the quality of reconstructed signal for classification task, we analyzed the performance of electrocardiogram (ECG) signal compression by comparing original and reconstructed signal on two problems. First, automatic sleep stage classification based on ECG signal; second, arrhythmia classification. Our experimental results showed that the accuracy of sleep stage classification and arrhythmia classification using reconstructed ECG signal from the proposed method is comparable to the original signal. The proposed method preserved signal characteristics for the automatic sleep stage and arrhythmia classification problems."

"ABSTRAKLossles data compression erat kaitannya engan masalah pengkodean. Bahkan inti dari kompresi data itu sendiri adalah pengkodean. Berbagai manipulasi data telah ditemukan oleh para ilmuwan di bidang lossless data compression. Salah satunya dan yang paling menarik adalah Burrows- Wheeler Transform (BWT) yang diambil dari nama dua penemuanya yaitu Michael Burrows dan David Wheeler. Hasil dari transformasi ini sangat bagus untuk proses pengkodean pada kompresi data.Skripsi ini mencoba merancang suatu kompresi data yang berbasis BWT dengan mempergunakan pengkodean konvensional Run Length Encoding, Move to Front Transform, dan Arithmetic Coding, kemudian coba diuji dan dianalisa performanya dibandingkan dengan standar program kompresi Linux gzip 1.3.3 agar dapat melihat kegunaan BWT tersebut."

"Digital video compression has revolutionised the broadcast industry. Its implementation has been the vital key to the expansion of video via satellite, cable, internet and terrestrial TV. However, new technologies not only enable new applications, they also create new challenges such as how to measure video quality, and how to maintain video quality in concatenated compression systems.Video Compression Systems provides an overview on many issues concerning today's complex digital video systems: from video quality measurements to statistical multiplexing, from pre-processing to transcoding and concatenation. It explains video compression systems from first principles and gives a detailed summary of currently used MPEG standards, as well as non-MPEG algorithms. Furthermore, it provides a summary of motion estimation algorithms and explains processing priorities for mobile applications, HDTV, contribution and distribution systems, as well as for end user systems.Video Compression Systems focuses intentionally on the principles rather than the mathematics in order to make it more readable and accessible to a wider audience. It is aimed at senior undergraduate students taking modules in video technologies, multimedia processing or video compression, as well as television engineers working on video compression systems."

"Visual communications services are now making a significant impact on modern society. Videoconferencing, HDTV and Multimedia are just examples where this technology is being used to good effect. Communicating using video signals does, however, require a large volume of data to be transmitted, and even with modern high-bandwidth communication links this can be expensive. This requires the implementation of efficient image or video coding and compression schemes. This paper presents image compression schemes using wavelet transform. This paper also highlights the importance of the four most desirable characteristics for use in digital signal processing, namely orthonormality, compactness, regularity or smoothness and symmetry or anti-symmetry. Some of these characteristics are mutually exclusive and require design compromise. From the simulation results it can be seen that for equal total length of the analysis (decomposition) and synthesis (reconstruction) filters, biorthonormal wavelets performs much better than the ortlionormal wavelet (i.e. asymmetrical wavelets). This performance is not only in terms of a higher WPSNR but also in terms of the quality of reconstructed image."