Automatic Ship Detection in SAR Images Using Multi-Scale Heterogeneities and an A Contrario Decision

Huang, Xiaojing; Yang, Wen; Zhang, Haijian; Xia, Gui-Song

doi:10.3390/rs70607695

Cited by 38 publications

(28 citation statements)

References 30 publications

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“…On the other hand, the selection of the Weibull function is justified by its flexibility in modelling many types of value distributions as indicated by [61]. This function has already been used in CD studies based on SAR images [62,63,64]. The results attained in this area have proven the feasibility of the Weibull distribution.…”

Section: Methodsmentioning

confidence: 99%

Assessment of Data Fusion Algorithms for Earth Observation Change Detection Processes

Molina

Martínez

Morillo

et al. 2016

Sensors

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In this work a parametric multi-sensor Bayesian data fusion approach and a Support Vector Machine (SVM) are used for a Change Detection problem. For this purpose two sets of SPOT5-PAN images have been used, which are in turn used for Change Detection Indices (CDIs) calculation. For minimizing radiometric differences, a methodology based on zonal “invariant features” is suggested. The choice of one or the other CDI for a change detection process is a subjective task as each CDI is probably more or less sensitive to certain types of changes. Likewise, this idea might be employed to create and improve a “change map”, which can be accomplished by means of the CDI’s informational content. For this purpose, information metrics such as the Shannon Entropy and “Specific Information” have been used to weight the changes and no-changes categories contained in a certain CDI and thus introduced in the Bayesian information fusion algorithm. Furthermore, the parameters of the probability density functions (pdf’s) that best fit the involved categories have also been estimated. Conversely, these considerations are not necessary for mapping procedures based on the discriminant functions of a SVM. This work has confirmed the capabilities of probabilistic information fusion procedure under these circumstances.

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Section: Methodsmentioning

confidence: 99%

Assessment of Data Fusion Algorithms for Earth Observation Change Detection Processes

Molina

Martínez

Morillo

et al. 2016

Sensors

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show abstract

“…Several international projects are investigating an operational ship monitoring system [1][2][3][4], and many experimental results are available on ship detection in SAR images [5][6][7][8][9][10]. In this ambit, ship wake detection not only has strong interest as the validation of ship presence, but also generates data useful for ship route estimation.…”

Section: Introductionmentioning

confidence: 99%

Wake Component Detection in X-Band SAR Images for Ship Heading and Velocity Estimation

2016

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Abstract:A new algorithm for ship wake detection is developed with the aim of ship heading and velocity estimation. It exploits the Radon transform and utilizes merit indexes in the intensity domain to validate the detected linear features as real components of the ship wake. Finally, ship velocity is estimated by state-of-the-art techniques of azimuth shift and Kelvin arm wavelength. The algorithm is applied to 13 X-band SAR images from the TerraSAR-X and COSMO/SkyMed missions with different polarization and incidence angles. Results show that the vast majority of wake features are correctly detected and validated also in critical situations, i.e., when multiple wake appearances or dark areas not related to wake features are imaged. The ship route estimations are validated with truth-at-sea in seven cases. Finally, it is also verified that the algorithm does not detect wakes in the surroundings of 10 ships without wake appearances.

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“…They are very time-consuming because global searching is an indispensable part in the processing. Moreover, with the rapid development of remote sensing technology, the resolution of remote sensing images increases, and the intensity, structure, shape and texture information are more abundant [5][6][7][8]. Due to the irregular shape, unfixed size and other characteristics of ROIs, the extraction accuracy cannot be guaranteed when Aggregating neighboring pixels into superpixels can not only reduce the complexity of subsequent processing but also maintain the boundary information.…”

Section: Introductionmentioning

confidence: 99%

Region-of-Interest Extraction Based on Local–Global Contrast Analysis and Intra-Spectrum Information Distribution Estimation for Remote Sensing Images

Zhang

Wang

2017

Remote Sensing

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Abstract:Traditional saliency analysis models have made great advances in region of interest (ROI) extraction in natural scene images and videos. However, due to different imaging mechanisms and image features, those approaches are not quite appropriate for remote sensing images. Thus, we propose a novel saliency analysis and ROI extraction method for remote sensing images, which is composed of local-global contrast analysis for panchromatic images and intra-spectrum information distribution estimation (LI) for multi-spectral images. The panchromatic image is first segmented into superpixels via level set methods to reduce the subsequent computation complexity and keep region boundaries. Then, the spatially weighted superpixel intensity contrast is calculated globally to highlight superpixels unique to others and obtain the intensity saliency map. In multi-spectral images, ROIs are often included in informative superpixels; therefore, the information theory is introduced to each spectrum independently to acquire the spectrum saliency map. The final result is obtained by fusing the intensity saliency map and the spectrum saliency map and enhancing pixel-level saliency. To improve the anti-noise properties, we employ the Gaussian Pyramid for multi-scale analysis, which removes noise points by the blurring operation and the down-sampling operation. Experiments were conducted aiming at comparing the LI model with nine competing models qualitatively and quantitatively. The results show that the LI model performs better in maintaining intact ROIs with well-defined boundaries and less outside interference, and it tends to be stable when faced with images contaminated by noise.

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Automatic Ship Detection in SAR Images Using Multi-Scale Heterogeneities and an A Contrario Decision

Cited by 38 publications

References 30 publications

Assessment of Data Fusion Algorithms for Earth Observation Change Detection Processes

Assessment of Data Fusion Algorithms for Earth Observation Change Detection Processes

Wake Component Detection in X-Band SAR Images for Ship Heading and Velocity Estimation

Region-of-Interest Extraction Based on Local–Global Contrast Analysis and Intra-Spectrum Information Distribution Estimation for Remote Sensing Images

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