This paper addresses the image denoising problem using a newly proposed digital image transform: the finite ridgelet transform (FRIT). The transform is invertible, non-redundant and achieved via fast algorithms. Furth...
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ISBN:
(纸本)0819437646
This paper addresses the image denoising problem using a newly proposed digital image transform: the finite ridgelet transform (FRIT). The transform is invertible, non-redundant and achieved via fast algorithms. Furthermore this transform can be designed to be orthonormal thus indicating its potential in many other imageprocessingapplications. We then propose various improvements on the initial design of the FRIT in order to make it to have better energy compaction and to reduce the border effect. Experimental results show that the new transform outperforms wavelets in denoising images with linear discontinuities.
Noise reduction has been a traditional problem in imageprocessing. Recent wavelet thresholding based denoising methods proved promising, since they are capable of suppressing noise while maintaining the high frequenc...
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ISBN:
(纸本)0780370414
Noise reduction has been a traditional problem in imageprocessing. Recent wavelet thresholding based denoising methods proved promising, since they are capable of suppressing noise while maintaining the high frequency signal details. However, the local space-scale information of the image is not adaptively considered by standard wavelet thresholding methods. In this paper, a new type of thresholding neural networks (TNN) is presented with a new class of smooth nonlinear thresholding functions being the activation function. Unlike the standard soft-thresholding function, these new nonlinear thresholding functions are infinitely differentiable. Then a new nonlinear 2-D space-scale adaptive filtering method based on the wavelet TNN is presented for noise reduction in images. The numerical results indicate that the new method outperforms the Wiener filter and the standard wavelet thresholding denoising method in both peak-signal-to-noise-ratio (PSNR) and visual effect.
In image watermarking, hybrid approaches increase imperceptibility and robustness. Also, a scaling factor is used, which should be optimized when combining the cover image and watermark. In this study, discrete wavele...
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ISBN:
(纸本)9781665450928
In image watermarking, hybrid approaches increase imperceptibility and robustness. Also, a scaling factor is used, which should be optimized when combining the cover image and watermark. In this study, discrete wavelet transform and discrete cosine transform (DCT) were used together. The watermark-edge image was obtained by randomly inserting the watermark on the horizontal, vertical and diagonal edge points of the cover image detected with Sobel. The DCT frequency components of the watermark-edge image were weighted with a generated matrix and combined with the DCT of the cover image. According to the obtained results, the proposed method is imperceptible and robust to various attacks, especially JPEG compression and noise attacks.
imageprocessing has gained an increased usage and impact in modern pavement networks automatic distress severity classification (DSC). DSC defines priorities and maintenance resources optimum allocation in order to a...
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ISBN:
(纸本)9781728133775
imageprocessing has gained an increased usage and impact in modern pavement networks automatic distress severity classification (DSC). DSC defines priorities and maintenance resources optimum allocation in order to achieve a cost-effective rehabilitation process. This paper presents a novel computer vision algorithm having the ability to process, isolate and evaluate the distress severity level of a pavement. A pavement color image is converted to grayscale and then processed for image denoising of the granularity and complex texture that represent and artifact in cracks edge detection. The processing is achieved by a 2D dual-tree double density wavelet transform filter banks that significantly reduces the granularity noise while preserving the pavement cracks for edge detection. The 2D wavelet FIR filters perform analysis, soft thresholding then a synthesis of the image. The second step is then an edge detection process followed by morphological filtering and labeled components size-histogram filter to isolate false edges as residuals of denoising. A final step is performed by two Savitzky-Golay filters for the detection of longitudinal and transverse alligator cracks projections. A weighted score function with multiple parameters is used for DSC.
This paper introduces a single-image super-resolution approach which is based on sparse representation over dictionaries learned in the wavelet domain. The diagonal detail subband learning and reconstruction is improv...
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ISBN:
(纸本)9781467355636;9781467355629
This paper introduces a single-image super-resolution approach which is based on sparse representation over dictionaries learned in the wavelet domain. The diagonal detail subband learning and reconstruction is improved by designing two diagonal dictionaries;one for the diagonal and another for the anti-diagonal orientations. Four pairs (low resolution and high resolution) of subband dictionaries are designed. The sparse representation coefficients for the respective low and high resolution images are assumed to be the same. The proposed algorithm is compared with the leading super-resolution techniques and is shown to excel both visually and quantitatively, with an average PSNR raise of 0.82 dB over the Kodak set. Moreover, this algorithm is shown to significantly reduce the dictionary learning computational complexity by designing compactly sized structural dictionaries.
In recent years wavelets have been quite successful in compression or denoising applications. To further improve the performance of wavelet based algorithms, we have recently introduced the notion of footprint, which ...
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ISBN:
(纸本)0780367251
In recent years wavelets have been quite successful in compression or denoising applications. To further improve the performance of wavelet based algorithms, we have recently introduced the notion of footprint, which is a data structure which contains all the wavelet coefficients generated by a discontinuity. The combined use of wavelets and footprints leads to very efficient algorithms for compression and denoising of 1-D piecewise smooth signals. In this paper, we extend some of the previous results. We present a new denoising;algorithm, where footprints are chosen adaptively according to the singularity locations. This new algorithm outperforms previously proposed ones. Then, we introduce the notion of edgeprints, which represents a natural extension of footprints to the two dimensional case. First experimental results on compression of 2-D piecewise smooth signal using edgeprints are promising.
In this paper, we propose image restoration algorithms based on adaptive wavelet-domain statistical models. We present a method to estimate the model parameters from the observations, and solve the restoration problem...
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ISBN:
(纸本)0780367251
In this paper, we propose image restoration algorithms based on adaptive wavelet-domain statistical models. We present a method to estimate the model parameters from the observations, and solve the restoration problem in orthonormal and translation-invariant wavelet domains. Substantial improvements over previous wavelet-based restoration methods are obtained. The use of a translation-invariant basis further enhances the restoration performance.
We introduce an isotropic measure of local contrast for natural images that is based on analytic filters and present the design of directional wavelet frames suitable for its computation. We show how this contrast mea...
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ISBN:
(纸本)0819437646
We introduce an isotropic measure of local contrast for natural images that is based on analytic filters and present the design of directional wavelet frames suitable for its computation. We show how this contrast measure can be used within a masking model to facilitate the insertion of a watermark in an image while minimizing visual distortion.
In this work we study a combination between wavelet transform and a model of the human visual system both from the mathematical and the computational point of view. We will combine the two procedures in such a way tha...
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ISBN:
(纸本)0819416274;9780819416278
In this work we study a combination between wavelet transform and a model of the human visual system both from the mathematical and the computational point of view. We will combine the two procedures in such a way that the computational complexity of the whole procedure is reduced for the maximum possible amount. The gaol is to improve the quality compression, by modelling the human visual system in the compression-decompression tasks. As a result, new filters for image compression are provided for any given multiresolution analysis, independently of the coding method adopted. The proposed algorithm has been applied to grey level images and compared to more traditional approaches which do not comprehend a modelization of the human visual system.
Based on lifting scheme and the construction theorem of biorthogonal wavelet, we propose a new symmetric biorthogonal 9/7-tap wavelet called LS97. Compared to Cohen-Daubechies-Feauveau 9/7-tap (CDF 9/7-tap) wavelet ad...
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ISBN:
(纸本)0780367251
Based on lifting scheme and the construction theorem of biorthogonal wavelet, we propose a new symmetric biorthogonal 9/7-tap wavelet called LS97. Compared to Cohen-Daubechies-Feauveau 9/7-tap (CDF 9/7-tap) wavelet adopted by JPEG2000, when new wavelet is applied to image coding, the compression performance is exactly the same as that of CDF 9/7-tap wavelet, while computational complexity is reduced remarkably.
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