Sch. of Electr. Eng., Cornell Univ., Ithaca, NY.
IEEE Trans Image Process. 1997;6(4):523-39. doi: 10.1109/83.563318.
Transmission of digital subband-coded images over lossy packet networks presents a reconstruction problem at the decoder. This paper presents two techniques for reconstruction of lost subband coefficients, one for low-frequency coefficients and one for high-frequency coefficients. The low-frequency reconstruction algorithm is based on inherent properties of the hierarchical subband decomposition. To maintain smoothness and exploit the high intraband correlation, a cubic interpolative surface is fit to known coefficients to interpolate lost coefficients. Accurate edge placement, crucial for visual quality, is achieved by adapting the interpolation grid in both the horizontal and vertical directions as determined by the edges present. An edge model is used to characterize the adaptation, and a quantitative analysis of this model demonstrates that edges can be identified by simply examining the high-frequency bands, without requiring any additional processing of the low-frequency band. High-frequency reconstruction is performed using linear interpolation, which provides good visual performance as well as maintains properties required for edge placement in the low-frequency reconstruction algorithm. The complete algorithm performs well on loss of single coefficients, vectors, and small blocks, and is therefore applicable to a variety of source coding techniques.
在有损分组网络上传输数字子带编码图像在解码器处呈现出重建问题。本文提出了两种用于重建丢失子带系数的技术,一种用于低频系数,一种用于高频系数。低频重建算法基于分层子带分解的固有特性。为了保持平滑性并利用高带内相关性,将三次插值曲面拟合到已知系数以插值丢失系数。通过根据存在的边缘在水平和垂直方向上自适应地调整插值网格来实现精确的边缘放置,这对于视觉质量至关重要。使用边缘模型来描述自适应,并且对该模型的定量分析表明,可以通过简单地检查高频带来识别边缘,而无需对低频带进行任何其他处理。高频重建使用线性插值完成,这不仅提供了良好的视觉性能,而且还保持了低频重建算法中边缘放置所需的特性。完整的算法在单个系数、向量和小块的丢失方面表现良好,因此适用于各种源编码技术。