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Motion Estimation Algorithm Using One-Bit-Transform with Smoothing and Preprocessing Technique

机译:具有平滑和预处理技术的一维变换运动估计算法

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A high performance 2D one-bit-transform (1BT) motion estimation algorithm with smoothing and preprocessing (S + P) is introduced in this paper. The 1BT technique is used to transform an 8-bit image into a 1-bit representation image (1BT image). In the 1BT motion estimation algorithm, the 8-bit current frame (c frame) and reference frame (p frame) are first transformed into their 1BT image respectively, before calculating the Sum of Absolute Difference (SAD) and performing the search operations using the Full Search Block Matching Algorithm (FSBMA). In our proposed algorithm, a smoothing threshold (Thresholds) is incorporated into the filtering kernel, which is used to perform the transformation from 8-bit image into the 1BT image. The smoothing technique can greatly reduce the scattering noise created in the 1BT image. This will help to improve the accuracy when performing the search operations. After the transformation, the 1BT image for the c frame and p frame is divided into number of macroblocks. The macroblock in the c frame will be first compared to the macroblock at the same position in the p frame. If the SAD is below the preprocessing threshold (Thresholdp), the macroblock is considered to have negligible movement and search operation is not required. This preprocessing technique can greatly reduce the total number of search operations. Simulation results show that an improvement up to 0.65 dB, with reduction in search operation up to 95.07% is achieved. Overall, the proposed S + P technique is very suitable to be used in applications such as video conferencing and monitoring.
机译:本文介绍了一种具有平滑和预处理(S + P)的高性能二维一比特变换(1BT)运动估计算法。 1BT技术用于将8位图像转换为1位表示图像(1BT图像)。在1BT运动估计算法中,首先先将8位当前帧(c帧)和参考帧(p帧)转换为它们的1BT图像,然后再计算绝对差之和(SAD)并使用完整搜索块匹配算法(FSBMA)。在我们提出的算法中,将平滑阈值(Thresholds)合并到过滤内核中,该内核用于执行从8位图像到1BT图像的转换。平滑技术可以大大减少1BT图像中产生的散射噪声。这将有助于提高执行搜索操作时的准确性。转换后,将c帧和p帧的1BT图像划分为多个宏块。首先将c帧中的宏块与p帧中相同位置的宏块进行比较。如果SAD低于预处理阈值(Thresholdp),则认为该宏块的运动可忽略不计,并且不需要搜索操作。这种预处理技术可以大大减少搜索操作的总数。仿真结果表明,实现了高达0.65 dB的改善,同时搜索操作减少了95.07%。总体而言,建议的S + P技术非常适合用于视频会议和监视等应用。

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