Algorithms, Complexity Analysis and VLSI Architectures for by Peter M. Kuhn

By Peter M. Kuhn

MPEG-4 is the multimedia normal for combining interactivity, traditional and artificial electronic video, audio and computer-graphics. general functions are: web, video conferencing, cellular videophones, multimedia cooperative paintings, teleteaching and video games. With MPEG-4 the next move from block-based video (ISO/IEC MPEG-1, MPEG-2, CCITT H.261, ITU-T H.263) to arbitrarily-shaped visible items is taken. this important step calls for a brand new technique for approach research and layout to fulfill the significantly larger flexibility of MPEG-4.
movement estimation is a vital a part of MPEG-1/2/4 and H.261/H.263 video compression criteria and has attracted a lot consciousness in learn and undefined, for the next purposes: it really is computationally the main hard set of rules of a video encoder (about 60-80% of the full computation time), it has a excessive influence at the visible caliber of a video encoder, and it isn't standardized, therefore being open to festival.
Algorithms, Complexity research, and VLSI Architectures for MPEG-4Motion Estimation covers intimately each step within the layout of a MPEG-1/2/4 or H.261/H.263 compliant video encoder:

  • Fast movement estimation algorithms
  • Complexity research instruments
  • Detailed complexity research of a software program implementation of MPEG-4 video
  • Complexity and visible caliber research of quick movement estimation algorithms inside of MPEG-4
  • Design house on movement estimation VLSI architectures
  • Detailed VLSI layout examples of (1) a excessive throughput and (2) a low-power MPEG-4 movement estimator.

Algorithms, Complexity research and VLSI Architectures for MPEG-4Motion Estimation is a crucial advent to varied algorithmic, architectural and process layout elements of the multimedia average MPEG-4. As such, all researchers, scholars and practitioners operating in photo processing, video coding or procedure and VLSI layout will locate this ebook of interest.

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This scheme determines the number of pixels compared on a frame-per-frame basis, controlled by the mean quantizer step-size of a frame. The authors showed that on average more than four bits can be truncated without affecting picture quality. DPC (Different Pixel Count) In [LeeC 96] the DPC (Different Pixel Count) scheme was proposed. Each pixel value of the current block and the search window is normalized using the mean of the current block pixel values followed by a quantization to a 2-bit resolution.

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The BFM matching criteria consists of the two parallel calculated features (these are compared for the current and the reference block), which are taken as cost function: 1. The mean, eq. 59), of a NxN block, which is the amplitude matching for the smoothness of the correlations among the subblocks [Xlee 96]. 2. The Hamming distance, eq. 60), of the binary sign vectors of a NxN block, which is a phase-template matching method to evaluate the roughness of matching differences within a block. The Hamming distance can be efficiently calculated by a XOR operation and a look-up table.

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