Information Systems Laboratory, Department of Electrical Engineering, Stanford University, Stanford, CA 94305-9510, USA.
IEEE Trans Image Process. 2000;9(5):760-72. doi: 10.1109/83.841513.
We propose a new efficient method for the design of orthogonal and biorthogonal lapped transforms for image coding applications. It is shown how perception related constraints such as decay and smoothness of the filters' impulse responses can be incorporated in the optimization procedure. A decomposition of lapped transforms (orthogonal and biorthogonal) with 50% overlap leads to an efficient recursive optimization procedure, which is robust with respect to initial solutions. The importance of this decomposition lies in the fact that it allows to decouple the design of the even-symmetric and the odd-symmetric filters and hence drastically reduces the number of variables to be optimized. It furthermore reveals all the variables predetermined by perception related and coding-efficiency related constraints imposed on the filters. We present design and coding examples demonstrating the perceptual performance and the rate distortion performance of the resulting transforms.
我们提出了一种新的有效方法，用于设计用于图像编码应用的正交和双正交拉普拉斯变换。结果表明，如何将与感知相关的约束（例如滤波器冲击响应的衰减和光滑性）合并到优化过程中。具有 50%重叠的拉普拉斯变换（正交和双正交）的分解导致有效的递归优化过程，该过程对初始解决方案具有鲁棒性。这种分解的重要性在于它允许解耦偶数对称和奇数对称滤波器的设计，从而大大减少了要优化的变量数。此外，它揭示了所有由滤波器施加的与感知相关和与编码效率相关的约束预先确定的变量。我们提出了设计和编码示例，展示了所得到的变换的感知性能和率失真性能。
