This paper proposes design schemes which obtain an efficient spare-channel assignment against single and double link failures for a self-healing network. Spare-channel design problems can be formulated as a linear-programming (LP) problem when variables are assumed to be continuous. For the problem, the proposed algorithm effectively solves a sub-set of whole constraints by making use of a maximum-flow algorithm in an iterative manner. It is shown that the maximum number of iteration times is limited by the number of links in the network. Moreover, the relation between the design function and the self-healing function is discussed. It is also shown that the cooperation of the two functions can realize more effective control in large scale networks.

The encoding of high quality and super high definition images requires new approaches to the coding problem. The nature of such images and the applications in which they are used prohibits the introduction of perceptible degradation by the coding process. In this paper, we discuss techniques for the perceptually transparent coding of images. Although technically lossy methods, images encoded and reconstructed using these techniques appear identical to the original images. The reconstructed images can be postprocessed (e.g., enhanced via anisotropic filtering), due to the absence of structured errors, commonly introduced by conventional lossy methods. The compression, ratios obtained are substantially higher than those achieved using lossless means.