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Contourlet

About: Contourlet is a research topic. Over the lifetime, 3533 publications have been published within this topic receiving 38980 citations.


Papers
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01 Jan 2012
TL;DR: A digital image watermarking algorithm in Wavelet, Contourlet and Curvelet transform domains is proposed that is invisible and robust against common image processing and attacks.
Abstract: In this paper a digital image watermarking algorithm in Wavelet, Contourlet and Curvelet transform domains is proposed. In the algorithm، original gray image is decomposed into coefficients in different sub-bands. For selected subband in each domain the watermark is embedded in the father nodes by relationship between father node and the maximum or minimum value of its child node. The experimental results show that the algorithm is invisible and robust against common image processing and attacks. Moreover it outperforms previous methods in the most situations.

9 citations

Proceedings ArticleDOI
01 Apr 2017
TL;DR: An extensive evaluation for the well-known clutter reduction algorithms with various scenarios to understand how these methods perform within the same framework is designed.
Abstract: Singular value decomposition (SVD), principal component analysis (PCA), and independent component analysis (ICA) are used as subspace based methods and curvelet transform (CT), nonsubsampled contourlet transform (NSCT) are used as multi-resolution based methods for clutter reduction algorithms in Ground-Penetrating Radar (GPR) images have been proposed in recent years with demonstrated success However, the datasets for evaluated clutter reduction algorithms are not the same and using different setups Thus, the performance result of algorithms in the literature are incomparable and sometimes contradictory To address these problems, we design an extensive evaluation for the well-known clutter reduction algorithms with various scenarios to understand how these methods perform within the same framework The methods are evaluated on the simulated data generated by the GprMax program A large library of simulated data is constructed by changing the three crucial parameters such as soil types, burial depths and material types in order to analyze the methods in depth The performance of both groups of methods are evaluated and results are reported in the sense of peak signal-to-noise (PSNR) for various scenarios

9 citations

Proceedings ArticleDOI
25 Sep 2009
TL;DR: This paper implements an acceleration system on a heterogeneous TI Da Vinci dual core processor consisting of an ARM processor core and a DSP processor core to carry out the time-consuming part of the contourlet transform.
Abstract: The classic wavelet transform has been applied in registration and fusion of medical images for decades. An extension namely, contourlet transform recently indicated its advantages in image fusion with better efficiency in multi-resolution and multi-direction representation and calculation. However, the even higher computational complexity it requires turns out to be a disastrous concern in embedded applications. In this paper, we implement an acceleration system on a heterogeneous TI Da Vinci dual core processor consisting of an ARM processor core and a DSP processor core. The ARM core controls the fusion procedure by extracting the luminance bits and invoking the DSP core to carry out the time-consuming part of the contourlet transform. The partitions of tasks are determined after the program is analyzed and profiled at functional level to make full use of the computational capability of the heterogeneous platform. Initial measured improved performance results are obtained and analyzed with projected further improvements.

9 citations

Journal ArticleDOI
TL;DR: A hybrid sub-band decomposition scheme for multispectral image fusion comprising of non-subsampled contourlet transform and shearlet transform domains is presented and the distinguishing fusion response of the proposed hybrid scheme has been validated by the comparisons done with the other fusion approaches.
Abstract: Multimodal medical image sensor fusion has revolutionized the medical analysis by improving the precision of computer assisted diagnosis. This is incorporated by highlighting the complementary information while minimizing the redundant content in the fused images from various biomedical sensors like MRI, Computed Tomography, and Positron Emission Tomography/Single-Photon Emission Computerized Tomography. Multispectral image fusion is a special case of multimodal fusion which serves to encompass both spatial and spectral details in the fused image. This paper presents a hybrid sub-band decomposition scheme for multispectral image fusion comprising of non-subsampled contourlet transform and shearlet transform domains. The pre-processing stage involves color transformation of an input multispectral image from red-green-blue to YIQ color space. Thereafter, both the source images (i.e., panchromatic and multispectral images) after sub-band decomposition are processed via the application of contrast enhancement, weighted-principal component analysis, and max-max algorithms. The low frequency coefficients are processed via phase congruency whereas a combination of directive contrast and normalized Shannon entropy is applied to high frequency coefficients. The objective assessment of image quality has been carried out using various reference and no-reference based performance metrics. The distinguishing fusion response of the proposed hybrid scheme has been validated by the comparisons done with the other fusion approaches.

9 citations

Journal ArticleDOI
TL;DR: A new image hiding method based on the contourlet transform that has a higher robustness against to common steganalysis approaches and the quality of stegano image has considerably improved in comparison with related state of the art methods.
Abstract: A new image hiding method based on the contourlet transform is proposed in this paper. This strategy is based on storing information in high frequency subbands of contourlet transform. The embedding approach is in direction that the contourlet sub-bands have the least statistical disorder. As a result, the proposed algorithm has a higher robustness against to common steganalysis approaches. In addition, the quality of stegano image has considerably improved in comparison with related state of the art methods, with the extracted secret image having an acceptable quality. Furthermore, the experimental results show robustness respect to Gaussian noise and other attacks such as JPEG compression. DOI: http://dx.doi.org/10.11591/ijece.v2i5.1433 Full Text: PDF

9 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
202336
202299
202175
2020109
2019155
2018164