A proficient video encoding system through a novel motion estimation algorithm

2011 Third International Conference on Advanced Computing Pub Date : 2011-12-01 DOI:10.1109/ICOAC.2011.6165165

S. A. Padmanabhan, S. Chandramathi

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引用次数: 4

Abstract

Video compression is a combination of spatial image compression and temporal motion compensation, which is mainly done for reducing the volume of data required to represent digital video images. Numerous video compression algorithms were proposed to reduce the data quantity and produced acceptable quality as possible as they can. In this research work, initially wavelet decomposition is applied to the I-frame and the resulting coefficients are quantized by means of a Listless SPECK (LSK) algorithm. Here, different wavelets namely, Daubechies, Coiflets, Biorthogonal, and Reverse Biorthogonal are utilized in the compression algorithm LSK. When different wavelets are used, the compression ratio is effectively changed according to the type of the wavelet. A new block motion estimation algorithm is employed to measure the motion between the blocks in the video. The performance analysis is done for evaluating the performance of proposed system with different wavelets. Moreover, the performance measures such as Compression Ratio (CR) and Peak Signal to Noise Ratio (PSNR) are calculated.

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通过一种新颖的运动估计算法，实现了一个熟练的视频编码系统

视频压缩是空间图像压缩和时间运动补偿的结合，主要是为了减少表示数字视频图像所需的数据量。人们提出了许多视频压缩算法，以尽可能减少数据量并产生可接受的质量。在本研究中，首先对i帧进行小波分解，然后利用Listless SPECK (LSK)算法对得到的系数进行量化。在这里，不同的小波即Daubechies, coiflet，双正交和反向双正交被用于压缩算法LSK。当使用不同的小波时，根据小波的类型有效地改变了压缩比。采用一种新的块运动估计算法来测量视频中块之间的运动。用不同的小波对系统的性能进行了评价。此外，计算了压缩比(CR)和峰值信噪比(PSNR)等性能指标。

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2011 Third International Conference on Advanced Computing

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