In this paper, a novel DWT-SVD perceptual fidelity metric for the evaluation of watermarking schemes is introduced. The proposed metric is based on a widely used Human Visual Model in the Discrete wavelet Transform do...
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In this paper, a novel DWT-SVD perceptual fidelity metric for the evaluation of watermarking schemes is introduced. The proposed metric is based on a widely used Human Visual Model in the Discrete wavelet Transform domain accounting for the frequency sensitivity, and the local luminance and contrast masking effects of the human eye. A relationship between the visual model in the DWT domain and the modification of the wavelet coefficients's singular values is derived. The proposed metric is validated through subjective assessment and its performance is compared to several state-of-the-art perceptual image distortion metrics. The paper focus on image Adaptive Watermarking methods in the Discrete wavelet Transform Domain since they yield better results regarding robustness and transparency than other watermarking schemes.
In this work, we have proposed a new image contrast enhancement technique based on complex wavelet transform (CWT) and singular value decomposition (SVD). The technique decomposes the input image into the eight freque...
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In this work, we have proposed a new image contrast enhancement technique based on complex wavelet transform (CWT) and singular value decomposition (SVD). The technique decomposes the input image into the eight frequency subbands by using CWT and estimates the singular value matrix of the real and complex low-low subbands, and then it reconstructs the enhanced image by applying the inverse CWT (ICWT). The technique is compared with the conventional image equalization techniques such as standard general histogram equalization (GHE) and local histogram equalization (LHE), as well as state-of-art technique such as Brightness Preserving Dynamic Histogram Equalization (BPDHE) and singular value equalization (SVE). The experimental results are showing the superiority of the proposed method over the conventional and the state-of-art techniques.
The goal of this study is to investigate how the moment based image normalization procedure that is used to increase robustness of a digital image watermark especially for geometrical attacks affects the capacity of a...
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The goal of this study is to investigate how the moment based image normalization procedure that is used to increase robustness of a digital image watermark especially for geometrical attacks affects the capacity of a digital image watermarking algorithm. For this purpose, watermark was inserted in discrete cosine and wavelet domains with and without normalization. Then, several attacks were performed on the watermarked images and the capacities of the resulting distorted images were estimated by using the statistical approach proposed by Moulin and Mihcak. Simulations show that the discrete wavelet transform always outperforms the discrete cosine transform.
It is known that in the field of image synthesis, multi-frame imageprocessing can produce better results than just single-image enhancement techniques. Such a technique uses similarity assessment to select the images...
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It is known that in the field of image synthesis, multi-frame imageprocessing can produce better results than just single-image enhancement techniques. Such a technique uses similarity assessment to select the images for synthesis. In this paper, we propose a new image similarity assessment index by using complex wavelet. It is found that the proposed index is robust to small rotations and translations as well as large intensity and contrast changes. Therefore, it can be widely applied in the field of image synthesis, especially high dynamic range imaging.
In this paper, we develop an intelligent application based neural networks and imageprocessing to recognize license plate for car management. Through the license recognition, the car number composed of English alphab...
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ISBN:
(纸本)9783642166952
In this paper, we develop an intelligent application based neural networks and imageprocessing to recognize license plate for car management. Through the license recognition, the car number composed of English alphabets and digitals is readable for computers. Recognition of license is processed in two stages including feature extraction and recognition. The feature extraction contains the image locating, segmentation of the region of interest (ROT). Then the extracted ROIs are fed to a trained neural network for recognition. The neural network is a three-layer feed-forward neural network. Test images are produced from real parking lots. There are 500 images of car plates with tile, zooming and various lighting conditions, for verification. The experiment results show that the ratio of successful locating of license plate is around 96.8%, and the ratio of successful segmentation is 91.1%. The overall successful recognition ratio is 87.5%. Therefore, the experimental result shows that the proposed method works effectively, and simultaneously to improve the accuracy for the recognition. This system improves the performance of automatic license plate recognition for future ITS applications.
This paper presents an alternative to the spatial reconstruction of the sampled color filter array acquired through a digital image sensor. A demosaicking operation has to be applied to the raw image to recover the fu...
This paper presents an alternative to the spatial reconstruction of the sampled color filter array acquired through a digital image sensor. A demosaicking operation has to be applied to the raw image to recover the full-resolution color image. We present a low-complexity demosaicking algorithm processing in the wavelet domain. Produced images are available at the output of the algorithm either in the spatial representation or directly in the wavelet domain for high-level post processing in the latter domain. Results show that the computational complexity has been lowered by a factor of five compared to state of the art demosaicking algorithms.
Communication via the Internet spreads out nowadays. Multimedia data such as image or video are aimed to be sent over the Internet without error. Multiple Description Coding (MDC) is an important coding/transmission m...
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Communication via the Internet spreads out nowadays. Multimedia data such as image or video are aimed to be sent over the Internet without error. Multiple Description Coding (MDC) is an important coding/transmission method that is developed to send the data over error-prone network. In this work, an optimal filtering approach is applied to a wavelet based MDC method that is commonly used in the literature. Experimental results show that the proposed approach provides better results in case of packet losses in the channel compared to conventional approaches.
However medical image archives are widely used, these archives are based on textual query. Recently, it is obtained successfully results in general purpose image archiving using content based image retrieval systems. ...
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However medical image archives are widely used, these archives are based on textual query. Recently, it is obtained successfully results in general purpose image archiving using content based image retrieval systems. Therefore, it has also began studying on content based retrieval in medical image archiving. In this study, it is investigated performances of features obtained from gray level co-occurrence matrix and wavelet transform for content based medical image retrieval. Finally, that it can be obtained using both methods is exposed.
In this paper, a wavelet based image watermarking scheme for copyright protection is proposed. In order to reduce the effect of synchronization errors caused by geometric attacks such as rotation, the watermark is emb...
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In this paper, a wavelet based image watermarking scheme for copyright protection is proposed. In order to reduce the effect of synchronization errors caused by geometric attacks such as rotation, the watermark is embedded into rotation normalized circular image, which is obtained from the host image. The embedding of the watermark is carried out by modifying the two largest coefficients values in selected blocks. The extraction process does not require the original image. Experimental results show that the proposed scheme successfully makes the watermark perceptually invisible as well as robust to common signalprocessing and some geometric attacks including JPEG compression, filtering sharpening, rotation and scaling attacks.
In this paper a wavelet-based logo watermarking scheme is presented. A binary logo is repeated in two dimensions and is used as a watermark. The watermark is embedded in the LLn sub-band of host image, using quantizat...
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In this paper a wavelet-based logo watermarking scheme is presented. A binary logo is repeated in two dimensions and is used as a watermark. The watermark is embedded in the LLn sub-band of host image, using quantization technique. The repetitive patterns of watermark are used to repairing of extracted watermark from distorted watermarked image. Knowing the quantization step-size, dimensions of logo and the level of wavelet transform, the watermark is extracted, without any need to have access to the original image. Robustness of the proposed algorithm was tested against the following attacks: JPEG2000 and old JPEG compression, adding salt and pepper noise, median filtering, rotating, cropping and scaling. The promising experimental results are reported and discussed.
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