Video coding is an imperative part of the modern day communication system. Furthermore, it has vital roles in the fields of video streaming, multimedia, video conferencing and much more. Scalable Video Coding (SVC) is an emerging research area, due to its extensive application in most of the multimedia devices as well as public demand. The proposed coding technique is capable of eliminating the Spatio-temporal regularity of a video sequence. In Discrete Bandelet Transform (DBT), the directions are modeled by a three-directional vector field, known as structural flow. Regularity is decided by this flow where the data entropy is low. The wavelet vector decomposition of geometrically ordered data results in a lesser extent of significant coefficients. The directions of geometrical regularity are interpreted with a two-dimensional vector, and the approximation of these directions is found with spline functions. This paper deals with a novel SVC technique by exploiting the DBT. The bandelet coefficients are further encoded by utilizing Set Partitioning in Hierarchical Trees (SPIHT) encoder, followed by global thresholding mechanism. The proposed method is verified with several benchmark datasets using the performance measures which gives enhanced performance. Thus, the experimental results bring out the superiority of the proposed technique over the state-of-arts.

中文翻译：

---

使用离散 Bandelet 变换的高效可扩展视频编码方法

视频编码是现代通信系统必不可少的一部分。此外，它在视频流、多媒体、视频会议等领域发挥着至关重要的作用。可扩展视频编码 (SVC) 是一个新兴的研究领域，由于其在大多数多媒体设备中的广泛应用以及公众需求。所提出的编码技术能够消除视频序列的时空规律。在离散 Bandelet 变换 (DBT) 中，方向由称为结构流的三个方向矢量场建模。规律性由数据熵低的这个流决定。几何有序数据的小波矢量分解导致较小程度的重要系数。几何规则的方向用二维向量解释，并且这些方向的近似值是用样条函数找到的。本文通过利用 DBT 来处理一种新颖的 SVC 技术。通过利用分层树中的集合分区 (SPIHT) 编码器对小带系数进行进一步编码，然后是全局阈值机制。所提出的方法通过几个基准数据集使用性能指标进行了验证，从而提高了性能。因此，实验结果表明所提出的技术优于现有技术。所提出的方法通过几个基准数据集使用性能指标进行了验证，从而提高了性能。因此，实验结果表明所提出的技术优于现有技术。所提出的方法通过几个基准数据集使用性能指标进行了验证，从而提高了性能。因此，实验结果表明所提出的技术优于现有技术。