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		<title><![CDATA[ Image Processing, IET - new TOC ]]></title>
		<link>http://ieeexplore.ieee.org</link>
		<description>TOC Alert for Publication# 4149689 </description>
		<year>2009</year>
		<month>November </month>
		<day>19</day>
		<item>
			<title><![CDATA[Distance measures for reduced ordering-based vector filters]]></title>
			<link><![CDATA[http://ieeexplore.ieee.org/xpls/abs_all.jsp?isnumber=5284326&arnumber=5284327]]></link>
			<description><![CDATA[Reduced ordering-based vector filters have proved successful in removing long-tailed noise from colour images while preserving edges and fine image details. These filters commonly utilise variants of the Minkowski distance to order the colour vectors with the aim of distinguishing between noisy and noise-free vectors. In this study, the authors review various alternative distance measures and evaluate their performance on a large and diverse set of images using several effectiveness and efficiency criteria. The results demonstrate that there are in fact strong alternatives to the popular Minkowski metrics.]]></description>
			<pubDate><![CDATA[October  2009]]></pubDate>
			<guid><![CDATA[http://ieeexplore.ieee.org/xpls/abs_all.jsp?isnumber=5284326&arnumber=5284327]]></guid>
			<volume>3</volume>
			<issue>5</issue>
			<startPage>249</startPage>
			<endPage>260</endPage>
			<fileSize>884</fileSize>
			<authors><![CDATA[Celebi, M.E.;]]></authors>
		</item>
		<item>
			<title><![CDATA[Improved parabolic prediction-based fractional search for H.264/AVC video coding]]></title>
			<link><![CDATA[http://ieeexplore.ieee.org/xpls/abs_all.jsp?isnumber=5284326&arnumber=5284328]]></link>
			<description><![CDATA[In this study, the authors propose an efficient fractional pixel search algorithm for H.264/AVC video coding to reduce the computational complexity in half/quarter-pixel motion estimation. A prediction for the optimal motion vector is derived under the assumption that the sum of absolute transform differences error surface is a symmetric parabolic function. With the optimal region, a decision rule for half-pixel search is proposed. The experimental result shows that approximately two search points are required. Based on the half-pixel search, a hierarchical quarter-pixel search is described and an extra three search points, on average, are consumed for each quarter-pixel search. Experimental results show that significant reduction in computation can be achieved, while maintaining high coding efficiency.]]></description>
			<pubDate><![CDATA[October  2009]]></pubDate>
			<guid><![CDATA[http://ieeexplore.ieee.org/xpls/abs_all.jsp?isnumber=5284326&arnumber=5284328]]></guid>
			<volume>3</volume>
			<issue>5</issue>
			<startPage>261</startPage>
			<endPage>271</endPage>
			<fileSize>696</fileSize>
			<authors><![CDATA[Lin, Y.;Wang, Y.C.;]]></authors>
		</item>
		<item>
			<title><![CDATA[Real-time video object segmentation in H.264 compressed domain]]></title>
			<link><![CDATA[http://ieeexplore.ieee.org/xpls/abs_all.jsp?isnumber=5284326&arnumber=5284329]]></link>
			<description><![CDATA[In this study the authors proposed a real-time video object segmentation algorithm that works in the H.264 compressed domain. The algorithm utilises the motion information from the H.264 compressed bit stream to identify background motion model and moving objects. In order to preserve spatial and temporal continuity of objects, Markov random field (MRF) is used to model the foreground field. Quantised transform coefficients of the residual frame are also used to improve segmentation result. Experimental results show that the proposed algorithm can effectively extract moving objects from different kinds of sequences. The computation time of the segmentation process is merely about 16 ms per frame for CIF size frame, allowing the algorithm to be applied in real-time applications.]]></description>
			<pubDate><![CDATA[October  2009]]></pubDate>
			<guid><![CDATA[http://ieeexplore.ieee.org/xpls/abs_all.jsp?isnumber=5284326&arnumber=5284329]]></guid>
			<volume>3</volume>
			<issue>5</issue>
			<startPage>272</startPage>
			<endPage>285</endPage>
			<fileSize>759</fileSize>
			<authors><![CDATA[Mak, C.-M.;Cham, W.-K.;]]></authors>
		</item>
		<item>
			<title><![CDATA[Incremental rate control for H.264/AVC video compression]]></title>
			<link><![CDATA[http://ieeexplore.ieee.org/xpls/abs_all.jsp?isnumber=5284326&arnumber=5284330]]></link>
			<description><![CDATA[In this study, the authors propose a new rate-complexity-quantisation model and an incremental rate control algorithm for H.264/AVC video coding. One unique property of this algorithm is that, the picture complexity estimation and rate-quantisation modelling are jointly designed with an incremental rate control for P-frames. In addition, the proposed algorithm also introduces a number of efficient rate control techniques, including accurate rate control for intra-frames, enhanced proportional--integral--derivative (PID) buffer controller, and adaptive quantisation parameter determination for B-frames. The proposed algorithm has low computational complexity while providing robust rate control. Our extensive experimental results demonstrate that the proposed algorithm outperforms the current rate control algorithm adopted in the H.264/AVC reference software JM13.2 by achieving more accurate rate control, reducing frame skipping, depressing quality fluctuation and improving the overall coding quality by up to 2.83 dB.]]></description>
			<pubDate><![CDATA[October  2009]]></pubDate>
			<guid><![CDATA[http://ieeexplore.ieee.org/xpls/abs_all.jsp?isnumber=5284326&arnumber=5284330]]></guid>
			<volume>3</volume>
			<issue>5</issue>
			<startPage>286</startPage>
			<endPage>298</endPage>
			<fileSize>773</fileSize>
			<authors><![CDATA[Sun, Y.;Zhou, Y.;Feng, Z.;He, Z.;Sun, S.;]]></authors>
		</item>
		<item>
			<title><![CDATA[Quad-splitting algorithm for a window query on a Hilbert curve]]></title>
			<link><![CDATA[http://ieeexplore.ieee.org/xpls/abs_all.jsp?isnumber=5284326&arnumber=5284331]]></link>
			<description><![CDATA[Space-filling curves, particularly, Hilbert curves, have been extensively used to maintain spatial locality of multi-dimensional data in a wide variety of applications. A window query is an important query operation in spatial (image) databases. Given a Hilbert curve, a window query reports its corresponding orders without the need to decode all the points inside this window into the corresponding Hilbert orders. Given a query window of size p x q on a Hilbert curve of size T x T, Chung et al. have proposed an algorithm for decomposing a window into the corresponding Hilbert orders, which needs O(n log T) time, where n = max(p,q). By employing the properties of Hilbert curves, the authors present an efficient algorithm, named as Quad-Splitting, for decomposing a window into the corresponding Hilbert orders on a Hilbert curve without individual sorting and merging steps. Although the proposed algorithm also takes O(n log T ) time, it does not perform individual sorting and merging steps which are needed in Chung et al.'s algorithm. Therefore experimental results show that the Quad-Splitting algorithm outperforms Chung et al.'s algorithm.]]></description>
			<pubDate><![CDATA[October  2009]]></pubDate>
			<guid><![CDATA[http://ieeexplore.ieee.org/xpls/abs_all.jsp?isnumber=5284326&arnumber=5284331]]></guid>
			<volume>3</volume>
			<issue>5</issue>
			<startPage>299</startPage>
			<endPage>311</endPage>
			<fileSize>652</fileSize>
			<authors><![CDATA[Wu, C.-C.;Chang, Y.-I.;]]></authors>
		</item>
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