Video compression with an effective block matching algorithm and RDOT

Dhananjay Kumar, V. Subbulakshmi
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Abstract

The storage requirement for digital video is growing day-by-day due to increase in video quality. In order to reduce the file size while maintaining the required quality, a novel compression algorithm is needed. In this paper, an Adaptive Rood Pattern Search (ARPS) is used as the Motion Estimation (ME) and Motion Compensation (MC) technique and ARPS is integrated with the proposed Rate Distortion Optimized Transform (RDOT) to reduce the computational complexity without losing the quality of the video. In this ME technique, Mean Absolute Difference (MAD) is considered as the matching criteria. ARPS technique is compared with the Diamond Search (DS) and Three Step Search (TSS) algorithms and it outperforms with respect to execution time and PSNR. Finally the combination of ARPS with RDOT achieves a high compression ratio.
视频压缩具有有效的块匹配算法和RDOT
由于视频质量的提高,对数字视频的存储需求日益增长。为了在保持所需质量的同时减小文件大小,需要一种新的压缩算法。本文采用自适应道路模式搜索(ARPS)作为运动估计(ME)和运动补偿(MC)技术,并将ARPS与所提出的率失真优化变换(RDOT)相结合,在不损失视频质量的前提下降低了计算复杂度。在这种方法中,平均绝对差(MAD)被认为是匹配标准。将ARPS技术与钻石搜索(DS)和三步搜索(TSS)算法进行比较,在执行时间和PSNR方面都优于ARPS算法。最后,ARPS与RDOT的结合获得了较高的压缩比。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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