A lossless data hiding scheme for medical images using a hybrid solution based on IBRW error histogram computation and quartered interpolation with greedy weights

Khosravi, Mohammad R.; Yazdi, Mehran

doi:10.1007/s00521-018-3489-y

Cited by 42 publications

(18 citation statements)

References 35 publications

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“…Thus, in addition to direct applications of interpolators such as magnification, interpolation is widely used for image restoration and reconstruction. In other researches, interpolation-based data hiding [8,14,15,18,25] and multispectral image fusion (pan-sharpening) [9] are carried out using it. For example in [9], LMMSE has been applied as a magnifier for achieving better quality in pan-sharpening process of Landsat-8 images compared to a linear interpolator.…”

Section: Related Workmentioning

confidence: 99%

“…Our purposed method uses an adaptive weighting mechanism which makes it edge-guided, non-linear, and fully greedy. Our scheme is an extension for the method discussed in [7][8][9] for remote sensing applications. In [7], a basic edge-guided interpolation based on linear minimum mean square error estimation (LMMSE) was introduced for benchmark images such that some evaluations about it have been done in [10].…”

Section: Introductionmentioning

confidence: 99%

“…We can also use the proposed approach for magnifying some multispectral images such as IKONOS and Quick-Bird images or images related to high-resolution optical remote sensing sensors [11][12][13]. In addition, there are many other applications for interpolation algorithms, e.g., data hiding [14][15][16][17][18], interpolation-based image denoising and demosaicking [19][20][21], SDTV to HDTV conversion (SD2HD) [2] in video processing, color processing [22], information fusion [8,9], and shadow detection [23] which can be assisted by ALMMSE algorithm. As we mentioned, the main focus of this research is towards interpolation-based image/video compression [10,24].…”

Section: Introductionmentioning

confidence: 99%

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Data compression in ViSAR sensor networks using non-linear adaptive weighting

Khosravi

Samadi

2019

J Wireless Com Network

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Nowadays, industrial video synthetic aperture radars (ViSARs) are widely used for aerial remote sensing and surveillance systems in smart cities. A main challenge of a group of networked ViSAR sensors in an IoT-based environment is low bandwidth of wireless links for communicating big video data. In this research, we propose a non-linear statistical estimator for adaptive reconstruction of compressed ViSAR data. Our proposed reconstruction filter is based on an adaptively generated non-linear weight mask of spatial observations. It can strongly outperform several conventional and well-known reconstruction filters for three different video samples.

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Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Data compression in ViSAR sensor networks using non-linear adaptive weighting

Khosravi

Samadi

2019

J Wireless Com Network

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“…The greater proportion of low value in H means the closer of two point sets, which indicates a better registration result. Therefore, the more points distribute within the low area means a better registration result [43].…”

Section: Data Fusion and Calculate Asdmentioning

confidence: 99%

Registration and fusion of 3D surface data from CT and ToF camera for position verification in radiotherapy

et al. 2019

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The purpose of this study is to introduce a low-cost method for verification of patient positioning before and during irradiation in radiotherapy. The experiments strategy is implemented by using a phantom like a human head in two modes: with and without thermoplastic masks. Radiotherapy is an effective clinical option for topical tumors treatment. Ability to the monitoring and control the patient's position during treatment is among the important items in radiotherapy. We registered to modality of 3D surface image in point cloud format, dynamic 3D image of time-of-flight camera (includes outer shape of head) and static 3D image of CT slice sectional by coherent point drift algorithm. Accuracy of 3D surface registration was calculated by average symmetrical surface distances (ASD) that it is a new method based on surface distance. The mean ASD calculated for rotation around X and Y axes of phantom is 2.62 ± 0.97 mm with immobilized thermoplastic mask and accuracy be increased to 1.69 ± 0.88 mm in non-thermoplastic mode. By performing paired T tests for ASDs, it was found that the use of a thermoplastic mask does not make a significant difference in the data acquisition. By developing this research to image fusion of that's 3D data sets, we will design to augmented reality in radiotherapy for verification of treatment planning and compare it with the electronic portal imaging device.

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“…Although the selected reference method is really powerful for quasi-sparse image data like ViSAR frames, however, we wish to improve its embedding capacity while keeping the final imaging quality as much as possible. The reference method can be followed in [3] and is a method based on interpolation-based data hiding (IBDH) towards watermarking using an interpolator and error histogram computation [4,5]. The core interpolator in our research is similar to [3], but some other interpolators can also be used, For example, in [6], the authors have provided a novel efficient optimization algorithm for treebased classification that can be adopted as a fast interpolator.…”

Section: Introductionmentioning

confidence: 99%

Efficient payload communications for IoT-enabled ViSAR vehicles using discrete cosine transform-based quasi-sparse bit injection

Khosravi

Samadi

2019

J Wireless Com Network

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High-performance remote sensing payload communication is a vital problem in airborne and space-borne surveillance systems. Among different remote sensing imaging systems, video synthetic aperture radar (ViSAR) is a new technology with lots of principal and managerial data which should be compressed, aggregated, and communicated from a radar platform (or a network of radars) to a ground station through wireless links. In this paper, a new data aggregation technique is proposed towards efficient payload transmission in a network of aerial ViSAR vehicles. Our proposed method is a combination of a recent interpolation-based data hiding (IBDH) technique and visual data transformation process using discrete cosine transform (DCT) which is able to outperform the reference method in terms of data aggregation ability.

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A lossless data hiding scheme for medical images using a hybrid solution based on IBRW error histogram computation and quartered interpolation with greedy weights

Cited by 42 publications

References 35 publications

Data compression in ViSAR sensor networks using non-linear adaptive weighting

Data compression in ViSAR sensor networks using non-linear adaptive weighting

Registration and fusion of 3D surface data from CT and ToF camera for position verification in radiotherapy

Efficient payload communications for IoT-enabled ViSAR vehicles using discrete cosine transform-based quasi-sparse bit injection

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