H.264 Mobile Video Application of Fast Block Matching Algorithm

H.264 Mobile Video Application of Fast Block Matching Algorithm
Authors:A.GOPI, D.VASAVIVANI

Abstract: This paper introduces Power consumption is very critical for portable video applications such as portable videophone and digital camcorder and also configurable motion estimation architecture for a wide range of fast block-matching algorithms (BMAs). Contemporary motion estimation architectures are either too rigid for multiple BMAs or the flexibility in them is implemented at the cost of reduced performance. The configurability of the proposed architecture is based on a new BMA framework that can be adjusted to support the desired set of BMAs. The total execution time of the mapped BMAs is shown to be almost directly proportional to the number of tested checking points in the search area, so the architecture is very tolerant of different BMA-specific search strategies and search patterns. We present an algorithm and hardware architecture for blockbased motion estimation that involves transforming video sequences from a multi bit to a one-bit/pixel representation and then applying conventional motion estimation search strategies. A performance comparison to the reference programmable architectures reveals that only the proposed implementation is able to process real-time (30 fps) fixed block-size motion estimation (1 reference frame) at full HDTV resolution (1920× 1080). 

Keywords: Motion Estimation, Multimedia, Video Compression Standards, H.264/MPEG, Fast BMA.

 INTRODUCTION 

            As The Multimedia and wireless technologies become mature, more and more sophisticated portable multimedia applications, such as video cellular phone and hand-held digital video camcorders, are becoming available. Real-time video compression is required to reduce the bandwidth, either for transmission or for storage of video data. However, it consumes a lot of power. Digital video is typically stored and transmitted in compressed form conforming to the MPEG standards for motion sequences. These standards utilize block-based motion estimation as a technique for exploiting the temporal redundancy in a sequence of images, thereby achieving increased compression. The simplest abstraction of the motion estimation problem is as follows. Given two blocks of pixels, a source block of size b * b and a search window larger than the source block, find the b * b sub block in the search window that is closest to the source block. The distance between two blocks can be measured by a number of different metrics and typically the l1 metric (mean absolute deviation) is used. Using this metric and a search strategy, we can evaluate candidate sub blocks of the search window to find the sub block that is closest to the source block.

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