7 research outputs found
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A low bit-rate video-coding algorithm based upon variable pattern selection
Recent research into pattern representation of moving regions in blocked-based motion estimation and compensation in video sequences, has focused mainly upon using a fixed number of regular shaped patterns. These are used to match the macroblocks in a frame that have two distinct regions involving static background and moving objects. In this paper a new Variable Pattern Selection (VPS) algorithm is presented which selects a preset number of best-matched patterns from a pattern codebook of regular shaped patterns. While more patterns are used than in the previous work, the performance of the VPS algorithm in using variable length coding, by exploiting the frequency of the best-matched patterns, leads to a higher compression ratio, without degrading the overall image quality
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Very low bit-rate video coding focusing on moving regions using three-tier arbitrary-shaped pattern selection algorithm
Very low bit-rate video coding using patterns to represent moving regions in macroblocks exhibits good potential for improved coding efficiency. Recently an Arbitrary Shaped Pattern Selection (ASPS) algorithm and its Extended version(EASPS) were presented, that used a dynamically extracted set of patterns, of the two different sizes, based on actual video content. These algorithms, like other pattern matching algorithms failed to capture a large number of active-region macroblocks (RMB) especially when the object moving regions is relatively larger in a video sequence. As the size of the moving object may vary, superior coding performance is achievable by using dynamically extracted patterns of a larger size. This paper, proposes a three-tier Arbitrary Shaped Pattern Selection (ASPS-3) algorithm that uses three different pattern sizes for very low bit ate coding. Experimental results show that ASPS-3 exhibits better performance compared with other pattern matching algorithms, including the low-bit rate video coding standard H.263
A very low bit-rate video coding algorithm by focusing on moving regions
2000-2001 > Academic research: refereed > Refereed conference paperVersion of RecordPublishe
Low Bit Rate Video Coding
Variable length bit rate (VLBR) broadly encompasses video coding which mandates a temporal frequency of 10 frames per second (fps) or less. Object-based video coding represents a very promising option for VLBR coding, though the problems of object identification and segmentation need to be addressed by further research. Pattern-based coding is a simplified object segmentation process that is computationally much less expensive, though a real-time, content-dependent pattern generation approach will certainly improve its acceptance for VLBR coding. In this paper pattern based coding technique is used. In this paper, a very low bit-rate video coding algorithm that focuses on moving regions is performed. The aim is to improve the coding performance, which gives better subjective and objective quality than that of the conventional coding methods at the same bit rate. Eight patterns are pre-defined to approximate the moving regions in a macroblock. The patterns are then used for motion estimation and compensation to reduce the prediction errors. Furthermore, in order to increase the compression performance, the residual errors of a macroblock are rearranged into a block with no significant increase of high-order DCT coefficients. As a result, both the prediction efficiency and the compression efficiency are improved. This paper shows that using pattern based coding the compression ratio is better
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A new efficient similarity metric and generic computation strategy for pattern-based very low bit-rate video coding
In the context of very low bit-rate video coding, pattern representations of a moving region (MR) in block-based motion estimation and compensation has become increasingly attractive. Generally, all existing pattern-matching algorithms apply a similarity metric, involving elementary operations, to compute the mismatch between an MR and a particular fixed pattern in order to select the best-matching pattern from a fixed-size codebook of predefined patterns. An efficient similarity metric, together with a new generic computation strategy, is presented by considering only the mismatch areas of MRs. It is theoretically proven that for a specific MR in a macroblock, the new similarity metric selects exactly the same pattern as existing metrics, while the resulting computational coding efficiency is improved by between 21% and 58% compared with the H.263 low bit-rate coding standard
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A real time generic variable pattern selection algorithm for very low bit-rate video coding
The selection of an optimal regular-shaped pattern set for very low bit-rate video coding, focusing on moving regions has been the objective of much recent research in order to try and improve bit-rate efficiency. Selecting the optimal pattern set however, is an NP hard problem. This paper presents a generic variable pattern selection (GVPS) algorithm, which introduces a pattern selection parameter that is able to control the performance in terms of computational complexity as well as bit-rate and picture quality. While using a sub-optimal variable pattern set, GVPS obtains a coding performance comparable to near-optimal algorithms, such as the k-change neighbourhood solution, while being much less computationally intensive, so that it is able to process all types of video sequences in real-time, with minimal pre-processing overheads