Original Full Resolution Research Articles

The global forest/non-forest map from TanDEM-X interferometric SAR data

In this paper we present the activities performed at the Microwaves and Radar Institute of the German Aerospace Center (DLR) to derive global forest/non-forest classification mosaics from interferometric synthetic aperture radar (InSAR) data acquired by the TanDEM-X mission. The data have been collected between 2011 and 2016 in bistatic stripmap single polarization (HH) mode, with the main goal of generating a consistent, timely, and highly accurate 3D representation of the global terrain’s surface (digital elevation model, DEM). The global data set of quicklook images, which represent a spatially averaged version of the original full resolution data at a ground independent pixel spacing of 50m×50m, was used as input, in order to limit the computational burden. For classification purposes, several observables, systematically provided by the TanDEM-X system, can be exploited, such as the calibrated amplitude, the digital elevation model (DEM), and the interferometric coherence. Among the several factors contributing to a coherence degradation in InSAR data, the so-called volume correlation factor quantifies the coherence loss due to volume scattering phenomena, which typically occur in presence of vegetation. This quantity is directly derived from the interferometric coherence and used as main indicator for the identification of vegetated areas. For this purpose, a fuzzy multi-clustering classification approach, which takes into account the geometry and acquisition configuration, is applied to each acquired scene separately. A certain variability of the interferometric coherence at X band was observed among different forest types, mainly due to changes in forest structure, density, and tree height, which led to an adjustment of the algorithm settings depending on the considered type of forest. The identification of additional information layers, such as urban settlements or water areas, is also discussed, and the procedure for mosaicking of overlapping acquisitions (two at global scale, up to ten over mountainous terrain, forests, and desert regions) to improve the classification accuracy is detailed. The resulting global forest/non-forest map was validated using external reference information as well as with other existing classification maps and an overall agreement was observed that often exceeds 90%. Finally, examples for high-resolution (at 12m×12m) forest maps and potentials for deforestation monitoring over selected regions are presented as well, demonstrating the unique capabilities offered by the TanDEM-X bistatic system for a broad range of geoinformation services and scientific applications. The global TanDEM-X forest/non-forest map presented in this paper will be made available to the scientific community for free download and usage.

Exploiting polarization using multi-frequency SAR data and multi-dimensional time-frequency techniques

During recent years, Time-Frequency (TF) techniques have been introduced to characterize scene polarimetric behaviours using PolSAR data. In this paper, we apply a TF decomposition approach to the analysis of PolSAR data with different frequency bands and show some polarimetric TF behaviours of various scenes. The PolSAR data may be decomposed in azimuth direction, range direction only and in both directions. Two statistical descriptor, i.e., polarimetric TF stationarity and coherence indicators, are used to depict the features of the scene backscattering response. Their individual performance is assessed. The polarimetric TF features, extracted from the scenes of interest, can show some special relevant information compared to the original full resolution case. Moreover, with the availability of new multi-frequency full-polarization high resolution F-SAR data, the results of same site with respect to different frequency bands are exploited and compared with each other.

Stereo Interleaving Video Coding With Content Adaptive Image Subsampling

Stereo interleaving video coding, in which both left and right view frames are subsampled into half size and multiplexed into one single frame before being encoded by a traditional 2-D video encoder, is an efficient encoding scenario for stereoscopic video. Many existing stereo interleaving video coding methods subsample each frame by utilizing fixed subsampling filter coefficients. Such methods are easy to implement; however, the varying property of the frame signal is ignored. By jointly considering the influences of subsampling and compression, a rate and distortion analysis about stereo interleaving video coding is proposed. The final distortion in stereo interleaving video coding is the summation of errors caused by subsampling (causing distortion between subsampling-interpolated image and the original full resolution one) and by quantization during compression. Based on the provided rate distortion analysis, a content adaptive image subsampling (CAIS) is also proposed. In CAIS, the half-size frames are generated by the optimal subsampling filters, which are calculated based on frame contents and the targeted interpolation coefficients. Experimental results demonstrate that the proposed CAIS is able to greatly improve compression efficiency of stereo interleaving video coding.

A flexible structure for fully scalable motion-compensated 3-D DWT with emphasis on the impact of spatial scalability

We investigate the implications of the conventional "t+2-D" motion-compensated (MC) three-dimensional (3-D) discrete wavelet/subband transform structure for spatial scalability and propose a novel flexible structure for fully scalable video compression. In this structure, any number of levels of "pretemporal" spatial wavelet decomposition are performed on the original full resolution frames, followed by MC temporal decomposition of the subbands within each spatial resolution level. Further levels of "posttemporal" spatial decomposition may be performed on the spatiotemporal subbands to provide additional levels of spatial scalability and energy compaction. This structure allows us to trade energy compaction against the potential for artifacts at reduced spatial resolutions. More importantly, the structure permits extensive study of the interaction between spatial aliasing, scalability and energy compaction. We show that where the motion model fails, the "t+2-D" structure inevitably produces misaligned spatial aliasing artifacts in reduced resolution sequences. These artifacts can be removed by using pretemporal spatial decomposition. On the other hand, we also show that the "t+2-D" structure necessarily maximizes compression efficiency. We propose different schemes to minimize the loss of compression efficiency associated with pretemporal spatial decomposition.