Denoising of SAR images

Matter of discussion in this Ph. D. thesis is SAR (Synthetic Aperture Radar) image denoising. Main elements of innovation are the introduction of SAR-BM3D, a denoising algorithm optimized for SAR data, and the introduction of a benchmark which enables the objective performance comparison of SAR denoising algorithms on simulated canonical SAR images. In the first part of the thesis, basic concepts on SAR images are introduced, with special emphasis on its peculiar multiplicative noise, called speckle. A description of key ideas and tools of denoising techniques known in literature then follows. After introducing the basic elements of SAR data processing, the main statistical features of SAR images are described, and it is clarified in which context the denoising techniques operate. Techniques are then classified as those that follow the homomorphic approach, where the multiplicative noise is turned into additive noise through a logarithmic transform, and those that take explicitly into account the multiplicative nature of noise. Afterwards, it is described how the introduction of the wavelet transform has brought new ideas into SAR image denoising and how the non-local filtering strategy, originally proposed in the AWGN field, has provided relevant results also in the application to SAR. In this context, the novel SAR-BM3D algorithm is introduced which, starting from key elements of wavelet-based and non-local filtering implemented in BM3D, optimizes the elaboration for SAR data, following a non-homomorphic approach. A very detailed experimental analysis on simulated SAR images, obtained as optical images corrupted by artificial speckle, has been performed: results proved the SAR-BM3D algorithm to outperform traditional approaches, both in terms of PSNR and visual inspection. Due to the well-known difficulties of evaluating the performance of denoising techniques on real SAR images, a workaround has been proposed. Rather than resorting to images corrupted by artificial speckle, a physical SAR simulator, SARAS (developed by the remote-sensing group of the Federico II University of Naples) has been used to generate a set of canonical benchmark SAR scenes. The main advantage of SARAS images is the availability of both the noisy and clean versions of the images, the latter acting as a reference to objectively evaluate the performances of different algorithms. We have shown in detail the procedure which leads to a definition of an objective criterion to compare results provided by different algorithms when working on real SAR images. For this purpose, different test cases have been selected and specific measures, suitable for the various scenes have been proposed for the characterization. At the end of the thesis, open issues are pointed out and future research is outlined

Sigmoid shrinkage for BM3D denoising algorithm

In this work we propose a modified version of the BM3D algorithm recently introduced by Dabov et al. [1] for the denoising of images corrupted by additive white gaussian noise. The original technique performs a multipoint filtering, where the nonlocal approach is combined with the wavelet shrinkage of a 3D cube composed by similar patches collected by means of block-matching. Our improvement concerns the thresholding of wavelet coefficients, which are subject to a different shrinkage depending on their level of sparsity. The modified algorithm is more robust with respect to block matching errors, especially when noise is high, as proved by experimental results on a large set of natural images

Application of denoising techniques to micro-tomographic images

Microcomputed tomography (microCT) is a particular version of computerized axial tomography commonly used by radiologists which reaches resolutions of the order of a few micrometers. In biology, this technique is especially useful for the study of hard tissues, such as calcified bone and dental matrices, because of their high linear attenuation coefficient. MicroCT images, though, are affected by a strong noise component, neither Gaussian nor white, caused by the characteristics of the acquisition system itself. In this paper we consider the problem of microCT image denoising, and compare the performance of two well-known denoising techniques and of BM3D, a recent technique based on the nonlocal approach. Although for the time being the performance analysis is mostly qualitative, results speak clearly in favor of BM3D

A nonlocal approach for SAR image denoising

Speckle reduction is a key step in several SAR image processing procedures. In this paper, a new despeckling technique based on the “nonlocal” denoising filter BM3D is presented. The filter has been modified in order to take into account SAR image characteristics. The experimental results, conducted on both synthetic and real SAR images, confirm the potential of the proposed approach

SAR image simulation for the assessment of despeckling techniques

We propose a new framework for the quantitative assessment of SAR despeckling techniques, based on physical-level simulation of SAR images corresponding to canonical scenes. Thanks to the simulator, we can generate multiple SAR images of the same scene which differ only in the speckle content, and, hence, a true multilook SAR image, with an arbitrarily large number of looks, to use as “speckle-free ” reference. Based on this concept, we select a small set of canonical scenes and, for each of them, a suitable set of objective measures which account for speckle suppression and image feature preservation. We gain insight into the system reliability by comparing the indications it gives for some sample despeckling filters with those obtained by expert visual inspection of the filtered images. Index Terms — Synthetic aperture radar (SAR), speckle reduction, quality assessment

Near Real-Time Volumetric Estimates Using Unmanned Aerial Platforms Equipped with Depth and Tracking Sensors

Volume estimation of specific objects via close-range remote sensing is a complex task requiring expensive hardware and/or significant computational burden, often discouraging users potentially interested in the technology. This paper presents an innovative system for cost-effective near real-time volume estimation based on a custom platform equipped with depth and tracking cameras. Its performance has been tested in different application-oriented scenarios and compared against measurements and state-of-the-art photogrammetry. The comparison showed that the developed architecture is able to provide estimates fully comparable with the benchmark, resulting in a quick, reliable and cost-effective solution to the problem of volumetric estimates within the functioning range of the exploited sensors