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Abstrak :
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.

Abstrak :
Kemajuan yang pesat di bidang telekomunikasi dewasa ini menyebabkan timbulnya berbagai jenis teknik kompresi yang dimanfaatkan dalam berbagai aplikasi. Teknik kompresi yang sangat dikenal saat ini adalah teknik kompresi DCT (discrete cosine transform) dengan metode scanning zig-zagnya. Teknik kompresi yang sedang dikembangkan saat ini adalah teknik kompresi dengan menggunakan transformasi wavelet. Dari perhitungan lama proses, nilai PSNR dan SNR, ternyata teknik kompresi transformasi wavelet memberikan hasil yang lebih bagus dibanding teknik kompresi dengan menggunakan DCT. Sampai saat ini belum ada pembakuan metode scanning yang cocok untuk diterapkan pada transformasi wavelet. Tesis ini membahas simufasi penerapan metode scanning vertikal, horisontal, zig-zag, dan diagonal pada kompresi gambar diam dengan menggunakan transformasi wavelet. Dengan membandingkan kinerja rasing-masing metode scanning, dalam hal ini parameter yang diperbandingkan adalah lama proses, jumlah koefisien yang di-scan, perhitungan RMSE temyata diperoleh bahwa metode scanning yang cocok untuk transformasi Wavelet adalah metode scanning zig-zag.

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Image compression is a process to reduce bit information of an image. The purpose of image compression is to obtain fewer amount of data and it can be reconstructed as a new image without decreasing its quality significantly. Image compression could be done in spatial domain or transformation domain. Wavelet transform is the effective methods for image compression process since its ability to localize the bit information contained of the image. One of the important steps in transformation image using wavelet transform is scanning step. To increase performance wavelet transform, choosing scanning method i.e. vertical, horizontal, zig-zag, and diagonal will be done. From analysis view depends on the composition of coefficient and time processing, it can be said that scanning method zig-zag give the best performance. ;Image compression is a process to reduce bit information of an image. The purpose of image compression is to obtain fewer amount of data and it can be reconstructed as a new image without decreasing its quality significantly. Image compression could be done in spatial domain or transformation domain. Wavelet transform is the effective methods for image compression process since its ability to localize the bit information contained of the image. One of the important steps in transformation image using wavelet transform is scanning step. To increase performance wavelet transform, choosing scanning method i.e. vertical, horizontal, zig-zag, and diagonal will be done. From analysis view depends on the composition of coefficient and time processing, it can be said that scanning method zig-zag give the best performance.

Abstrak :
Pada dasarnya, tujuan kompresi gambar adalah bagaimana mendapatkan nilai rasio kompresi rasio yang tinggi, tepat dan gambar rekonstruksi masih dapat dikenali oleh visual manusia. Penentuan rasio kompresi secara tepat adalah hal yang penting dilakukan karena nilai rasio kompresi berhubungan dengan media penyimpanan serta waktu pengiriman gambar. Dengan menggunakan metoda klasifikasi kuantisasi vektor, nilai rasio kompresi yang diinginkan mempunyai range (sebaran) yang besar dan dapat diperkirakan sehingga dijadikan masukan simulasi. Metoda klasifikasi kuantisasi vektor adalah metoda kuantisasi vektor dengan membagi data kedalam blok-blok (sel) ukuran tertentu dan menghasilkan kode yang mewakili blok-blok tersebut dengan cara mengambil data dengan jarak atau distorsi terkecil menurut klasifikasi orientasi subband horizontal, vertikal dan diagonal. Kode itu disebut dengan codebook. Dengan menggunakan metoda klasifikasi kuantisasi vektor, sebagai masukan simulasi adalah nilai variabel rasio kompresi 4,8,16,32 dan 64 maka diperoleh hasilnya adalah gambar rekonstruksi masih dapat dikenali dengan baik pada nilai rasio kompresi 4, 8, 16 dan 32 dimana nilai PSNR masih > 30 dB. Sedangkan nilai rasio kompresi 64, gambar rekonstruksi sudah tidak dapat dikenali lagi karena nilai PSNR sudah < 30 dB sehingga gambar rekonstruksinya mengalami penurunan kontras yang menyebabkan kabur dan bertambahnya efek blocking.

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Basically, the image compression is to achieve high compression ratio, accurate and recognized image reconstruction. Achieving compression ratio accurately is somewhat important to accomplish. Normally, compression ratio is defined by determining PSNR. By using classification of quantization vector method, getting the compression ratio is likely to do. The unique of this method is that this method can be arranged from 4 up to 64 of compression ratio. The classification of quantization vector method is one of vector quantization methods that classify image data to specified block and process the blocks to produce the representative block by taking minimum distance or distortion according to horizontal, vertical and diagonal energy. Those codes are codebooks. By using the classification of quantization vector method combining with the compression ratio value as an input variable of 4,8,16,32 and 64, the outcome is that reconstructed images of the compression ratio ranged 4, 8,16 and 32 is good with PSNR > 30 dB whereas the compression ratio of 64 is not recommended (PSNR value < 30 dB) for any images particularly for textures images.

Abstrak :
Pada Tugas Akhir ini akan membahas teknik kompresi video codec yang mampu melakukan kompresi data frame mencapai ≥ 50% dari frame originalnya. Adapun tahapan kompresi input stream video dibagai menjadi 3 tahapan:

1. Pengurangan keseragaman spatial yang terjadi pada komponen-komponen intensity dalam suatu image.
2. Pengurangan keseragaman temporal yang terjadi pada motion object di frame-1, frame-2, frame-3 dan seterusnya.
3. Entropy coding untuk mengurangi energi komponen image yang kurang significant.

Dari tahapan diatas maka teknik kompresi yang didesign pada video codec disusun menjadi 3 sub-block besar : Transform coding yang menggunakan 2D-DCT, motion compensator berbasis pada SAD algorithm, dan RLE ( Run Length Encoding). Untuk mengetahui unjuk kerja system video codec yang telah didesign maka diperlukan pengukuran sesuai standart pengukuran ITU-T tentang kualitas video kompresi yaitu [8] :

1. Pengukuran secara subjectif dengan metode DSCQS (double stimulus continuous quality scale).
2. Pengukuran secara objectif dimana tool yang digunkan adalah PSNR (peak signal to noise ratio) dan MSE (mean squared error).

Dari hasil pengukuran teknik kompresi video didapatkan hasil PSNR yang masih jauh diatas ambang batas minimal yang diperbolehkan oleh ITU-T yaitu 20 dB. ...... This project will discuss about video codec compression that will compress data frame to 50% smaller from it original size. There are three main steps to compress video stream input :

1. Reducing spatial similarity occurred in intensity components from source image.
2. Reducing temporal similarity occurred in motion object at first frame, second frame, third frame, etc.
3. Entropy coding to eliminate less significant image component energy.

From those steps mentioned above, design compression technique at video codec will rebuilt in to three major sub block : Transform coding using 2D-DCT, motion compensator based on SAD algorithm, and RLE (Run Length Encoding). To analyze performance of video codec systems that have been designed, measurable success indicator based on ITU-T standardization on video compression quality will be needed. Those indicator are [8]:

1. Subjective measurements using DSCQS (Double Stimulus Continuous Quality Scale) Method.
2. Objective measurements using PSNR (peak signal to noise ratio) and MSE (mean squared error) as it tools.

Using those video compression measurements above, this project resulting PSNR value above its minimal threshold described in ITU-T (20dB).

Abstrak :
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.

Abstrak :
Pati singkong terpregelatinasi telah dibuat melalui proses pemanasan suspensi pati di atas suhu gelatinasinya. Tujuan penelitian ini adalah untuk mengetahui kemampuan pregelatinasi pati singkong mensubstitusi mikrokristal selulosa sebagai diluen, pengikat dan desintegrator (eksipien) tablet yang dibuat dengan cara cetak langsung, menggunakan parasetamoll sebagai model obat dengan lima formula. Tiga formula mengandung campuran mikrokristal selulosa (MS) dan pregelatinasi pati singkong (PPS), satu formula mengandung MS dan satu formula lagi mengandung PPS. Tablet yang dihasilkan dievaluasi kekerasan, keregasan, daya hancur dan laju disolusi. Hasil evaluasi menunjukkan bahwa semakin tinggi jumlah PPS yang digunakan semakin keras tablet yang dihasiikan dan semakin sukar hancur dalam saluran pencernaan, akan tetapi semakin tinggi jumlah MS dalam tablet semakin rendah laju disolusi zat berkhasiat.

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Pregelatinization tapioca starch has been made by heating tapioca starch suspension above its gelatinization temperature. The aim of this research was to determine the ability of pregelatinized tapioca starch (PTS) as a binder, filler or a disintegrator in direct compression tablet for replacing microcrystallines cellulose (MC) as excipient in tablet. It has been carried out five formulas which paracetamol as a model drug. Three formulas consist of MC and PTS in variety concentrations, one formula consist of MC only, and the other one formula is PTS only. The quality of tablet depends on the hardness, friability, disintegration, and dissolution rate. The results showed that PTS can increase the hardness of tablet, while MC makes the solution rate decreased.

Abstrak :
Dengan bertambahnya pembangunan gedung-gedung pencakar langit di Jakarta, maka kedalaman fondasi yang dapat menopang kekuatan gedung-gedung tersebut semakin diperlukan. Walaupun telah banyak dilakukan penyelidikan tanah yang mencapai kedalaman lebih dari 100 meter untuk kebutuhan design, tetapi belum banyak studi akademik mengenai data dari hasil penyelidikan tanah tersebut. Di Jakarta, terutama di daerah Jalan Thamrin dan Sudirman, terdapat banyak gedung-gedung tinggi, di mana pada kedalaman 30-150 meter sering ditemukan jenis tanah lempung teguh. Tesis ini akan membahas mengenai jenis tanah lempung teguh Jakarta dengan berfokus pada parameter kompresi atau konsolidasi dari jenis tanah ini. ......With the increased population of high-rise buildings in Jakarta, deeper foundation is required to support these buildings’ weight. Although deep soil investigation has been done for more than 100m depth for design purposes, there are not many academic studies for this kind of soil. At Thamrin and Sudirman Street, where most skyscraper buildings are located, stiff clay layer can be found at 30-150m depth. This thesis will focus on compression or consolidation parameter for this deep layer stiff clay.

Abstrak :
Dalam komunikasi multimedia khususnya dalam format video, dibutuhkan sumber daya yang tepat agar diperoleh kualitas gambar yang diinginkan. Ketersediaan bandwidth dan resolusi perangkat yang berbeda-beda pada sisi client serta teknik kompresi yang digunakan untuk transmisi juga berpengaruh secara signifikan terhadap kualitas video. Meskipun standar kompresi video H.264/AVC dan ekstensinya yaitu scalabe video coding SVC diperkenalkan dan berhasil menjawab tantangan tersebut, ternyata masih terdapat kelemahan khususnya untuk transmisi video dengan resolusi tinggi. Besarnya ukuran bitstream yang dihasilkan standar SVC untuk kompresi video resolusi ultra tinggi, hanya bisa dipenuhi kualitasnya jika ditransmisikan pada jaringan dengan bandwidth yang besar. Untuk itu, dalam perkembangannya standar kompresi H.265 HEVC dan ekstensinya yaitu scalable high efficiency video coding SHVC diperkenalkan untuk mengatasi permasalahan pada standar SVC. Standar kompresi video baru tersebut terbukti dapat mengurangi kebutuhan bandwidth sampai dengan 50 dibandingkan dengan standar SVC untuk kualitas video yang sama. Pada penelitian ini, analisa kinerja transmisi video terskala standar SHVC dilakukan dengan membandingkan dengan standar SVC. Pengujian dilakukan dengan mengemulasikan kedua teknik kompresi video melalui emulator jaringan Mininet-Wifi untuk mendapatkan gambaran transmisi sesungguhnya. Dengan menerapkan skenario uji transmisi video client-server dengan bandwidth berbeda-beda, dan posisi client diatur pada jarak yang berbeda-beda dari access point-nya, didapatkan bahwa waktu transmisi, packet loss, dan kualitas video rekonstruksi pada transmisi video terskala dengan standar SHVC lebih baik dibandingkan pada transmisi video terskala dengan standar SVC. ......Video communication requires the right resources to obtain the desired image quality. Availability of bandwidth and screen resolution from different devices on the client end, as well as compression techniques used for transmission also significantly influence to the video quality. Even the H.264 AVC video compression standard and its scalable extension known as scalable video coding SVC was introduced and successfully addressed the challenge, there are some weakness especially on high resolution video transmissions. The size of the bitstream generated by the SVC standard for ultra high resolution video compression can only be met if transmitted on a network with a large bandwidth. Therefore, in its development the H.265 HEVC compression standard and its extension known as scalable high efficiency video coding SHVC were introduced to overcome problems in the SVC standards. The new video compression standard is proven to reduce bandwidth requirements by up to 50 compared to SVC standards for the same video quality. This study introduces the performance analysis of SHVC standard video transmission as compared to SVC standard. Both compression standards are transmitted and emulated through network emulator called Mininet Wifi to get the real transmission picture. The client server video transmission scheme with different bandwidth, and variation of client position different distances from access point are set in the experiment scenario. It is found that transmission time, packet loss, and video reconstruction quality on scalable video transmission with SHVC standard is better than scalable video transmissions with SVC standards.