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A Biorthogonal Transform With Overlapping and Non-Overlapping Basis Functions for Image Coding

机译:具有重叠和非重叠基函数的双正交变换,用于图像编码

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摘要

This paper presents a novel design method of a biorthogonal lapped transform that consists of long (overlapping) and short (nonoverlapping) basis functions (VLLBT), which can reduce the annoying blocking artifacts and ringing. We formulate the VLLBT by extending conventional lapped transforms. Then, we provide the theory of the Karhunen-Loeve transform in a subspace (SKLT). Using the theory of the SKLT, we show that given biorthogonal long basis functions of the VLLBT, the optimal short basis functions in the energy compaction sense are derived by solving an eigenvalue problem without iterative searching techniques. This leads to a desirable feature from a parameter optimization of view since the degree of freedom for the VLLBT can be theoretically reduced by means of the SKLT. Moreover, the SKLT enables us to easily construct a two-dimensional (2-D) VLLBT with nonseparable short basis functions. Experimental results show that compared to the case where all parameters are optimized, the reduction of free parameters by using the SKLT cause no decline in coding gain for the AR(1) process, and the proposed transform provides promising performance in coding efficiency of images.
机译:该文提出了一种由长(重叠)和短(非重叠)基函数(VLLBT)组成的双正交搭接变换设计方法,可以减少烦人的阻塞伪影和振铃。我们通过扩展传统的搭接变换来制定 VLLBT。然后,我们提供了子空间中的Karhunen-Loeve变换理论(SKLT)。利用SKLT理论,我们证明了给定VLLBT的双正交长基函数,通过求解特征值问题,在没有迭代搜索技术的情况下推导了能量压缩意义上的最优短基函数。从参数优化的角度来看,这导致了一个理想的特征,因为理论上可以通过SKLT降低VLLBT的自由度。此外,SKLT使我们能够轻松构建具有不可分离短基函数的二维(2-D)VLLBT。实验结果表明,与所有参数均优化的情况相比,使用SKLT减少自由参数对AR(1)过程的编码增益没有下降,并且所提出的变换在图像编码效率方面提供了良好的性能。

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