Region-adaptive probability model selection for the arithmetic coding of video texture

In video coding systems using adaptive arithmetic coding to compress texture information, the employed symbol probability models need to be retrained every time the coding process moves into an area with different texture. To avoid this inefficiency, we propose to replace the probability models used in the original coder with multiple switchable sets of probability models. We determine the model set to use in each spatial region in an optimal manner, taking into account the additional signaling overhead. Experimental results show that this approach, when applied to H. 264/AVC's context-based adaptive binary arithmetic coder (CABAC), yields significant bit-rate savings, which are comparable to or higher than those obtained using alternative improvements to CABAC previously proposed in the literature

A separate least squares algorithm for efficient arithmetic coding in lossless image compression

The overall performance of discrete wavelet transforms for losssless image compression may be further improved by properly designing efficient entropy coders. In this paper a novel technique is proposed for the implementation of context-based adaptive arithmetic entropy coding. It is based on the prediction of the value of the current transform coefficient. The proposed algorithm employs a weighted least squares method applied separately for the HH, HL and LH bands of each level of the multiresolution structure, in order to achieve appropriate context selection for arithmetic coding. Experimental results illustrate and evaluate the performance of the proposed technique for lossless image compression

Increased compression efficiency of AVC and HEVC CABAC by precise statistics estimation

The paper presents Improved Adaptive Arithmetic Coding algorithm for application in future video compression technology. The proposed solution is based on the Context-based Adaptive Binary Arithmetic Coding (CABAC) technique and uses the authors’ mechanism of symbols probability estimation that exploits Context-Tree Weighting (CTW) technique. This paper proposes the version of the algorithm, that allows an arbitrary selection of depth of context trees, when activating the algorithm in the framework of the AVC or HEVC video encoders. The algorithm has been tested in terms of coding efficiency of data and its computational complexity. Results showed, that depending of depth of context trees from 0.1% to 0.86% reduction of bitrate is achieved, when using the algorithm in the HEVC video encoder and 0.4% to 2.3% compression gain in the case of the AVC. The new solution increases complexity of entropy encoder itself, however, this does not translate into increase the complexity of the whole video encoder

A multiresolution approach for the coding of edges of still images using adaptive arithmetic coding

International audienceAn edge coding scheme based on chain code representation in a multiresolution image coding context is presented. Our method enhances the coding schemes that describe the source structure with Markov models, by using also an a priori knowledge from the previous decoded resolution images. Experiments using adaptive arithmetic coding have shown up to a 5% improvement for the bitrate compared to a Markovian scheme

Motion estimation and CABAC VLSI co-processors for real-time high-quality H.264/AVC video coding

Real-time and high-quality video coding is gaining a wide interest in the research and industrial community for different applications. H.264/AVC, a recent standard for high performance video coding, can be successfully exploited in several scenarios including digital video broadcasting, high-definition TV and DVD-based systems, which require to sustain up to tens of Mbits/s. To that purpose this paper proposes optimized architectures for H.264/AVC most critical tasks, Motion estimation and context adaptive binary arithmetic coding. Post synthesis results on sub-micron CMOS standard-cells technologies show that the proposed architectures can actually process in real-time 720 × 480 video sequences at 30 frames/s and grant more than 50 Mbits/s. The achieved circuit complexity and power consumption budgets are suitable for their integration in complex VLSI multimedia systems based either on AHB bus centric on-chip communication system or on novel Network-on-Chip (NoC) infrastructures for MPSoC (Multi-Processor System on Chip

Implementasi Arithmetic Coding Menggunakan Modeler Prediction by Partial Matching Pada Kompresi File Teks.

ABSTRAKSI: Kebutuhan tempat penyimpanan data dan kebutuhan bandwidth yang meningkat menyebabkan diperlukannya sistem kompresi yang dapat memampatkan data sehingga tempat penyimpanan data atau penggunaan bandwidth dapat lebih dioptimalkan. Salah satu metode dalam proses pemampatan data adalah Arithmetic Coding. Arithmetic Coding adalah salah satu cara untuk memampatkan data berdasarkan pada entropy atau probabilitas dari data atau simbol yang dibaca. Dalam melakukan kompresi, Arithmetic Coding membutuhkan modeler yang digunakan untuk menyediakan distribusi probabilitas dari simbol untuk dikodekan. Salah satu modeler yang digunakan dalam menyediakan distribusi probabilitas adalah Prediction by Partial Matching (PPM). PPM merupakan modeler yang menyediakan tabel probabilitas berdasarkan konteks, atau disebut juga context modeling.Pada tugas ini akan dimplementasikan sistem kompresi Arithmetic Coding menggunakan PPM pada file teks. Selain itu juga akan diimplementasikan sistem kompresi menggunakan model Zero Order yang digunakan sebagai pembanding untuk mengetahui peningkatan peformansinya.Setelah dilakukan pengukuran secara obyektif maka ditarik kesimpulan bahwa sistem kompresi Arithmetic Coding PPM menghasilkan rasio lebih baik hampir setengah dari rasio kompresi Arithmetic Coding menggunakan Zero Order yaitu 48,32%, akan tetapi durasi yang dihasilkan mengalami peningkatan rata-rata (lebih lama) sebesar 132,87%, dan untuk kecepatan rata-rata mengalami penurunan sebesar 84,70% jika dibandingkan Arithmetic Coding menggunakan model Zer Order.Kata Kunci : Kompresi file teks, Arithmetic Coding, Prediction by Partial Matching, Zero Order, Context Modeling.ABSTRACT: Needs of data storage and bandwidth requirements causing the need for compression system which can compress data thus the space of data storage or bandwidth usage can be optimized. One method of data compression is Arithmetic Coding. Arithmetic Coding is a technique to compress the data based on entropy or probability of data or symbol that are read. Arithmetic Coding requires modeler that is used to providing probability distributions of symbol to be encoded. Prediction by Partial Matching is a modeler that provides distribution probability based on context, or also known as context modeling.In this final project will be implemented Arithmetic Coding compression systems using Prediction by Partial Matching on text files and also will be implemented compression system using Zero Order model that is used as a comparative to the increase in peformance.After using objective measurement, finally conclude that Arithmetic Coding compression systems generate PPM better ratio nearly half of the compression ratio using a Zero Order Arithmetic Coding about 48.32%, but for average of duration has increased (over time) by 132.87 %, and for the average speed decreased by 84.70% compared to Arithmetic Coding using model Zer Order.Keyword: Text Compression, Arithmetic Coding, Prediction by Partial Matching, Zero Order, Context Modeling

High-speed EBCOT with dual context-modeling coding architecture for JPEG2000

[[abstract]]This work presents a parallel context-modeling coding architecture and a matching arithmetic coder (MQ coder) for the embedded block coding (EBCOT) unit of the JPEG2000 encoder. The tier-1 of the EBCOT consumes most of the computation time in a JPEG2000 encoding system, and the proposed parallel architecture can increase the throughput rate of the context-modeling. To match the high throughput rate of the parallel context-modeling architecture, and efficient pipelined architecture for context-based adaptive arithmetic encoder is proposed. This encoder of JPEG2000 can work at 185MHz to encode one symbol each cycle. Compared with the conventional context-modeling architecture, our parallel architecture can decrease the execution time about 25%.[[conferencetype]]國際[[conferencedate]]20040523~20040526[[conferencelocation]]溫哥華, 加拿