context model造句
例句與造句
- we study the context modeling in lossless image compression
研究了無損圖像壓縮中的context模型設(shè)計(jì)問題。 - context modeling is a key point in compression algorithm designing
context模型是無損壓縮算法設(shè)計(jì)中關(guān)鍵部分，它對算法壓縮性能至關(guān)重要。 - this algorithm is composed of the predictor and rice coding based on context modeling
該算法設(shè)計(jì)了專門的預(yù)測器和基于上下文建模的rice編碼。 - below we elaborate personal networking related issues in internet protocols, context modelling, and configuration management
下面，我們展開個(gè)人網(wǎng)絡(luò)相關(guān)的，在互聯(lián)網(wǎng)協(xié)議，環(huán)境建模和配置管理方面的議題。 - in this second part of personal networking challenges i will address three key enablers : internet protocols, context modelling and configuration management
在個(gè)人網(wǎng)絡(luò)挑戰(zhàn)的第二部分，我將解決三個(gè)關(guān)鍵使能因素：互聯(lián)網(wǎng)協(xié)議，環(huán)境建模和配置管理。 - It's difficult to find context model in a sentence. 用context model造句挺難的
- on the basis of chinese syntactic analysis and semantic analysis, we construct a model of chinese context, called chinese context model ( ccm )
在漢語句法分析和語義分析的基礎(chǔ)之上，本文建立了漢語上下文語境模型ccm(chinesecontextmodel，ccm)。 - inspired by glicbawls, calic, ececow, and ezw coding schemes, a new context model of wavelet coefficients for image compression is proposed
受glicbawls、calic、ececow和ezw編碼方法的啟發(fā)，本文提出了一種新的用于圖像壓縮的小波系數(shù)的上下文模型(pcw)。 - we analysis and make comparison among several frequently adopted context models in lossless compression algorithm for image . image compression framework based on integral wavelet is proposed and implemented
本文首先介紹了相關(guān)標(biāo)準(zhǔn)及所使用的context模型，然后對連續(xù)色調(diào)??即灰度和彩色圖像無損壓縮中常用的context模型進(jìn)行了分析討論。 - so there ’ s a great correlation among the second bitplane . so we offered a new arithmetic coding scheme in which the design of context models is based on level and bitplane . considering the difference between luma and chroma coefficients, we will make it separately
由于abslevel=1的高概率出現(xiàn),使得第二位平面具有很大的相關(guān)性,因此文中算術(shù)編碼的上下文模型的設(shè)計(jì)方案主要基于level值和bitplane。 - this paper presents a algorithm that combined unary code and exp-golomb code . it switched separately in consideration of the difference between luma and chroma coefficients, instead of setting a marking bit which will bing loss at the same time, and also added some corresponding context models . it had been tested on sd, hd and cif, three types of sequence, and the bitrate had been saved by 1.24134 %, 0.10016 % and 0.16029 % on average
針對這種情況,本文引入exp-golomb碼來減少較大的變換系數(shù)二值化的冗余問題,提出了一種unary碼和exp-golomb碼相結(jié)合的的二進(jìn)制化算法,該算法避免了設(shè)立標(biāo)志位所帶來的附加損耗,分別針對于變換系數(shù)中的luma系數(shù)和chroma系數(shù)的概率分布特點(diǎn),采取了不同的自適應(yīng)切換設(shè)置,并且相應(yīng)地增加了概率模型。 - inspired by typical coding schemes such as ezw, spiht, ebcot, 3d-iezw, 3d-spiht and 3d-escot, a new context model of wavelet coefficients is proposed, which make use of partial order, self-similarity between subbands of wavelet coefficients and the correlation of neighboring wavelet coefficients
受ezw、spiht、ebcot模型及3d-ezw、3d-spiht、3d-escot模型的啟發(fā)，本文綜合利用小波系數(shù)不同子帶間的自相似性、偏序性和同子帶內(nèi)相鄰系數(shù)的相關(guān)性，提出了一種新的三維小波嵌入編碼上下文模型3d-pem。 - they all are snr scalable, and, especially ebcot is resolution scalable . these properties are essential in transmission of image on internet . because the performance of an entropy coder can be significantly improved by having the coder dynamically adapt to the current " context ", context models also have widely been adopted in image compression
基于小波的圖像壓縮已成為圖像壓縮研究的主流，一些小波系數(shù)模型也隨之產(chǎn)生，如ezw、spiht和用于jpeg2000的ebcot，這三種模型都具有snr可擴(kuò)展性質(zhì)，其中ebcot還具有分辨率可擴(kuò)展性質(zhì)。 - there have been two type of embedded coding . the first is based on partial order and self-similarity between subbands of wavelet coefficients, which organizes the wavelet coefficients across subbands into a zerotree, while the second is based on context models, using the correlation of neighboring wavelet coefficients
目前，嵌入編碼都是基于兩種類型：一種是分層的嵌入編碼，主要是利用小波不同子帶間系數(shù)的偏序性和自相似性，將不同子帶間的系數(shù)形成一棵棵樹結(jié)構(gòu)，通過將整棵樹量化為零來減少壓縮比。 - therefore, the main subject of this paper is to design a universal, low complexity, lossless and near-lossless compression algorithm for biomedical signals, fith a series of techniques, including context modeling, adaptive prediction and golomb coding, our algorithm obtains satisfactory results on various kinds of biomedical signals with low complexity of implementation
從上述考慮出發(fā)，本課題研究設(shè)計(jì)了一個(gè)通用、低復(fù)雜性的生物醫(yī)學(xué)信號無損近無損壓縮算法。通過采用上下文建模、自適應(yīng)預(yù)測和golomb編碼等一系列技術(shù)，該壓縮算法對各類生物醫(yī)學(xué)信號都獲得了較好的壓縮效果，達(dá)到了通用、低復(fù)雜性的設(shè)計(jì)要求。