Reconstruction Of Missing Information Research Articles

Sparse-based reconstruction of missing information in remote sensing images from spectral/temporal complementary information

Because of sensor failure and poor observation conditions, remote sensing (RS) images are easily subjected to information loss, which hinders our effective analysis of the earth. As a result, it is of great importance to reconstruct the missing information (MI) of RS images. Recent studies have demonstrated that sparse representation based methods are suitable to fill large-area MI. Therefore, in this paper, we investigate the MI reconstruction of RS images in the framework of sparse representation. Overall, in terms of recovering the MI, this paper makes three major contributions: (1) we propose an analysis model for reconstructing the MI in RS images; (2) we propose to utilize both the spectral and temporal information; and (3) on this basis, we make a detailed comparison of the two kinds of sparse representation models (synthesis model and analysis model). In addition, experiments were conducted to compare the sparse representation methods with the other state-of-the-art methods.

Reconstruction-Based Subband Image Coding for UDP Transmissions over the Internet

Quality-delay trade-offs can be made in transmitting subband-coded images in the Internet by using either the TCP or the UDP protocol. Delivery by TCP gives superior decoding quality but with very long delays when the network is unreliable, whereas delivery by UDP has negligible delays but with degraded quality when packets are lost. Although images are delivered primarily by TCP today, we study in this paper the use of UDP to deliver multi-description reconstruction-based subband-coded images and the reconstruction of missing information at the receiver based on information received. We first determine empirically the interleaving factors that should be used in order to keep the probability of unrecoverable packet losses sufficiently small. Next, we propose a joint sender-receiver approach for designing transforms in multi-description subband coding. In the receiver, we use a simple interpolation-based reconstruction algorithm, as sophisticated concealment techniques cannot be employed in practice. In the sender, we design an optimized reconstruction-based subband transform (ORB-ST), with an objective of minimizing the mean squared error, assuming that some of the descriptions are lost and that the missing information is reconstructed by simple averaging at the destination. Experimental results show that our proposed ORB-ST performs well in real Internet tests, and UDP delivery of MDC images is an attractive alternative to TCP delivery.