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26th IEEE signal processing and Communications applications Conference, SIU 2018

作者： Üstübioǧlü, Arda Ulutaş, Guzin Üstübioǧlü, Beste Bilgisayar Mühendisliǧi Karadeniz Teknik Üniversitesi Trabzon Turkey

ISBN: (纸本)9781538615010

During transmission of medical images over the network security problems arise due to confidentiality, verification and integrity. Medical image watermarking(MIW) is a technology developed to solve these security problems. In this paper, a new medical image watermarking algorithm based on Integer Discrete wavelet Transform (IDWT) and Fast Walsh-Hadamard Transform (FWHT) is proposed. Tamper localization and image authentication is performed with the Block Authentication Vector (BAV) and logo information which are embedded into the medical image. In the proposed method, the attacks to be performed in the ROI can be detected in a small region such as 4×4. Higher NC values, average 48.5db PSNR and lower computational time obtained in the experimental results indicate the effectiveness of the proposed method. © 2018 IEEE.

关键词： Discrete wavelet transforms

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Adaptive image Watermarking Algorithm Based on an Efficient Perceptual Mapping Model

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IEEE ACCESS 2018年 6卷 66254-66267页

作者： Taha, Taha Basheer Ngadiran, Ruzelita Ehkan, Phaklen Univ Malaysia Perlis Sch Comp & Commun Engn Arau 02600 Malaysia

Watermark imperceptibility is a significant requirement for keeping watermarked images looking perceptually similar to the original ones. Effective watermark imperceptibility requires the creation of a perceptual model that simulates the human visual system to efficiently hide the watermark in places where the human eye cannot observe it. Current perceptual-based watermarking models use complex computations that are difficult to implement in embedded systems or in real-time applications. In this paper, a low-complexity, integer-based lifting wavelet transform was utilized to create a perceptual mapping model that mainly relies on a new texture mapping model called accumulative lifting difference (ALD). The ALD is combined with a simplified edge detection and luminance masking models to obtain a comprehensive perceptual mapping model that has high-noise tolerance and it is based on low-complexity calculations. The proposed model was 7% faster than the fastest pixel-based compared model with an enhanced average peak signal-to-noise ratio (PSNR) gain of 2.78 dB. In comparison to the largest noise tolerance compared sub-band model, the proposed just noticeable distortion model had a PSNR gain of 1.8 dB and an execution speed that was 90% faster. The perceptual model is utilized in a proposed image watermarking algorithm to determine the maximum watermark embedding intensity that is not visible to the human eye. The experimental results show that the proposed algorithm produced high-quality watermarked images and was robust against different geometric and non-geometric attacks. In addition to its usage in watermarking, the new perceptual model can be used in various image processing and real-time applications.

关键词： Accumulative lifting differences image watermarking lifting wavelet transform perceptual mapping texture masking

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基于小波变换的滤波方法的研究与应用

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数字技术与应用 2020年第10期38卷 25-26页

作者：张丽丽张伟丹东东方测控技术股份有限公司辽宁丹东118000

小波分析是近年来一种新颖的应用于信号处理的数学方法,不论是在图像处理还是信号处理中,都有重要的应用。本文通过介绍了小波分析的基本理论,提出了小波分析在信号滤波方面的设计与应用。相比于传统的非线性滤波器中值滤波,小波去噪的... 详细信息

小波分析是近年来一种新颖的应用于信号处理的数学方法,不论是在图像处理还是信号处理中,都有重要的应用。本文通过介绍了小波分析的基本理论,提出了小波分析在信号滤波方面的设计与应用。相比于传统的非线性滤波器中值滤波,小波去噪的滤波方式更能够有效地消除瞬时脉冲对信号的干扰。文本通过超声波检测回波实例分析,通过不同滤波方案的波形与信噪比的比对证明,以中值-小波变换相结合的方式进行滤波,获得更好的滤波效果。

关键词：小波分析信号处理滤波超声检测

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image FUSION USING BELIEF PROPAGATION

IMAGE FUSION USING BELIEF PROPAGATION

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IEEE International Conference on Acoustics, Speech and signal processing (ICASSP)

作者： Hill, Paul Bull, David Univ Bristol Dept Elect & Elect Engn Bristol BS8 1UB Avon England

ISBN: (纸本)9781538646588

This paper describes the application of belief propagation methods to image fusion within a complex wavelet decomposition (the Dual Tree Complex wavelet Transform: DT-CWT). Belief propagation within each transform subband iterates through a lattice based Bayesian belief network. This leads to precisely controlled spatial coherence of subband coefficient fusion through the definition of belief graph probabilities. This results in a significant improvement in quantitatively measured fusion performance for a large database of over 160 fusion image pairs from a range of fusion applications including remote sensing, multi-focus and multi-modal sources. Improvements in qualitative image fusion performance is also demonstrated.

关键词： image Fusion wavelets Bayesian Belief Networks Bayesian Belief Propagation

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Improved Adaptive wavelet Thresholding for Effective Speckle Noise Reduction in Low Contrast Medical images

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JOURNAL OF CIRCUITS SYSTEMS AND COMPUTERS 2019年第10期28卷

作者： Sreelatha, P. Ezhilarasi, M. KGiSL Inst Technol Dept Elect & Commun Engn Coimbatore 641035 Tamil Nadu India Kumaraguru Coll Technol Dept Elect & Instrumentat Coimbatore 641049 Tamil Nadu India

Informative images endure from poor contrast and noise during image acquisition. Significant information retrieval necessitates image contrast enhancement and removal of noise as a prerequisite before any further processing can be done. Dominant applications with low contrast images affected by speckle noise are medical ultrasound images. The objective of this work is to improve the effectiveness of the preprocessing stage in medical ultrasound images by enhancing the image while retaining its structural characteristics. For image enhancement, this work proposes to develop an automatic contrast enhancement technique using cumulative histogram equalization and gamma correction based on the image. For noise removal, this work proposes an algorithm Gamma Correction with Exponentially Adaptive Threshold (GCEAT) which suggests the use of GC for contrast enhancement along with a new wavelet-based adaptive soft thresholding technique for noise removal. The proposed GCEAT-based image de-noising is validated with other enhancement and noise removal techniques. Experimental results with low contrast synthetic and actual ultrasound images show that the suggested proposed system performs better than existing contrast enhancement techniques. Encouraging results were obtained with medical ultrasound images in terms of Peak-signal to Noise Ratio (PSNR), Mean Square Error (MSE), Structural Similarity Index Measure (SSIM) and Average Intensity (AI).

关键词： Adaptive wavelet threshold contrast enhancement cumulative histogram equalization gamma correction image metrics speckle reduction ultrasound medical imaging

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Effective Color image watermarking scheme using YCbCr color space and QR code

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MULTIMEDIA TOOLS AND applications 2018年第10期77卷 12655-12677页

作者： Patvardhan, C. Kumar, Pragyesh Lakshmi, C. Vasantha Dayalbagh Educ Inst Dept Elect Engn Agra Uttar Pradesh India Dayalbagh Educ Inst Dept Phys & Comp Sci Agra Uttar Pradesh India

A digital image watermarking technique is proposed to hide the relevant information in color digital images. The image is converted from RGB color space to YCbCr color space. This enables the algorithm to exploit characteristics of the Human Visual System (HVS) for embedding the watermark. The scheme embeds the watermark information utilizing wavelets transforms and Singular Value Decomposition (SVD) for this purpose. It uses a Quick Response (QR) code as the watermark. The QR code is a robust code from which embedded information can be extracted even if the retrieved QR code image is distorted. Thus the proposed technique employs a judicious combination of different algorithmic ideas including altered YCbCr color space, transformation into wavelet domain, SVD for selection of places to embed and QR codes for enhanced robustness. The watermarking scheme proposed is robust against various signal processing attacks (e.g. filtering, compression, noise addition etc.) as well as geometric attacks (e.g. rotation, cropping etc.). Computational experiments on a variety of cover images show that embedding QR code is more effective than the other watermarks in terms of better information carrying capacity, robustness and imperceptibility. The proposed scheme is novel and effective as it simultaneously provides advantages of each of the individual elements combined in this approach.

关键词： Digital image watermarking YCbCr color model QR code wavelet transform Color image

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Multifractal Parameters in Prediction of Land-use Components on Satellite images

Multifractal Parameters in Prediction of Land-use Components...

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signal processing Algorithms, Architectures, Arrangements and applications (SPA)

作者： Wojciech Drzewiecki Anna Wawrzaszek Michał Krupiński Sebastian Aleksandrowicz Małgorzata Jenerowicz AGH University of Science and Technology Krakow Poland Centrum Badań Kosmicznych Polskiej Akademii Nauk Warsaw Poland

ISBN: (纸本)9781728139906

The aim of the study was to assess the usefulness of multifractal parameters as global features describing the content of very high-resolution satellite images. It was done in a research experiment aiming at prediction of basic land-use classes shares within the image tiles cut from satellite EROS-A images. The reference land use data were obtained by on-screen digitizing of aerial ortophotomaps. The shares of built-up areas, agriculture areas and forests in the area of every image tile (ca. 1 sq. km) were calculated. image tiles were also characterized using wide set of selected global textural features. Apart from multifractal parameters and fractal dimension we used histogram-based features as well as parameters based on co-occurrence matrix, run length matrix, absolute gradient, autoregressive model and wavelet analysis. The Cubist algorithm was applied to predict the percentages of each land use class within the image tiles. The results were evaluated using RMSE, MAE and R squared. When particular groups of textural parameters are considered, the best results in our experiment were obtained for absolute gradient-based features and multifractal features. The outcomes of presented study confirmed our previous findings that multifractal parameters should be considered as useful descriptors of high-resolution satellite image content.

关键词： Fractals Satellites Remote sensing Predictive models Agriculture Forestry wavelet analysis

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The role of the coarsest resolution subband in the wavelet-based reconstruction of signals from gradients 10

The role of the coarsest resolution subband in the wavelet-b...

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10th International Conference on Computer and Electrical Engineering

作者： Sevcenco, Ioana S. Agathoklis, Panajotis Univ Victoria Elect & Comp Engn Dept Victoria BC Canada

An efficient wavelet-based algorithm to reconstruct non-square/non-cubic signals from gradient data is proposed. This algorithm is motivated by applications such as image or video processing in the gradient domain. In some earlier approaches, the non-square/non-cubic gradients were extended to enable a square/cubic Haar wavelet decomposition and the coarsest resolution subband was derived from the mean value of the signal. In this paper, a nonsquare/non-cubic wavelet decomposition is obtained directly without extending the gradient data. The challenge comes from finding the coarsest resolution subband of the wavelet decomposition and an algorithm to compute this is proposed. The performance of the algorithm is evaluated in terms of accuracy and computation time, and is shown to outperform the considered earlier approaches in a number of cases. Further, a closer look on the role of the coarsest resolution subband coefficients reveals a trade-off between errors in reconstruction and visual quality which has interesting implications in image and video processing applications.

关键词： wavelet decomposition

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A novel hybrid of DCT and SVD in DWT domain for robust and invisible blind image watermarking with optimal embedding strength

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MULTIMEDIA TOOLS AND applications 2018年第11期77卷 13197-13224页

作者： Kang, Xiao-bing Zhao, Fan Lin, Guang-feng Chen, Ya-jun Xian Univ Technol Fac Printing Packaging Engn & Digital Media Techn Dept Informat Sci Xian 710048 Shaanxi Peoples R China

To optimize the tradeoff between imperceptibility and robustness properties, this paper proposes a robust and invisible blind image watermarking scheme based on a new combination of discrete cosine transform (DCT) and singular value decomposition (SVD) in discrete wavelet transform (DWT) domain using least-square curve fitting and logistic chaotic map. Firstly cover image is decomposed into four subbands using DWT and the low frequency subband LL is partitioned into non-overlapping blocks. Then DCT is applied to each block and several particular middle frequency DCT coefficients are extracted to form a modulation matrix, which is used to embed watermark signal by modifying its largest singular values in SVD domain. Optimal embedding strength for a specific cover image is obtained from an estimation based on least-square curve fitting and provides a good compromise between transparency and robustness of watermarking scheme. The security of the watermarking scheme is ensured by logistic chaotic map. Experimental results demonstrate the better effectiveness of the proposed watermarking scheme in the perceptual quality and the ability of resisting to conventional signal processing and geometric attacks, in comparison with the related existing methods.

关键词： Robust blind watermarking Discrete wavelet transform Discrete cosine transform Singular value decomposition Least squares curve fitting Logistic chaotic map

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Low SNR Sonar image Restoration Based on Mixed Probability Statistical Model in wavelet Domain

Low SNR Sonar Image Restoration Based on Mixed Probability S...

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IEEE International Conference on Big Data and Cloud Computing (BdCloud)

作者： Ping Xia Qiang Ren Dong-xia Shi Bang-jun Lei Yao-bin Zou Guang-zhu Xv Hubei Key Laboratory of Intelligent Vision based Monitoring for Hydroelectric Engineering College of Computer and Information Technology Three Gorges University YiChang China

ISBN: (数字)9781728143286

ISBN: (纸本)9781728143293

Since it is difficult to get texture details for sonar image denoising with strong noise and weak feature information. A sonar image enhancement algorithm in wavelet domain based on Gaussian mixture model and Gaussian mixture model is proposed to preserve the weak feature information of the sonar image. Under strong noise interference, the traditional enhancement method has certain difficulties in measuring the similarity of the details of the sonar image. For this reason, wavelet multi-scale analysis is performed on the sonar image to extract the weak feature information of each resolution. Secondly, a directed probability map model between adjacent scales in the wavelet domain is constructed to realize the similar weak feature information association. According to the parent node state probability and the transition probability matrix, the state values of the corresponding child nodes are determined, and the relationship between the state information of parent and child node is constructed. Thirdly, the Gaussian mixture model is used to fit the wavelet coefficient state distribution, and the neighborhood coefficient correlation is used to describe the relationship between the weak feature information in the scale. Finally, the wavelet coefficient estimation of the restored image signal is calculated by the state probability obtained in the expectation maximization (EM) algorithm, and the sonar image is reconstructed. The results of the contrast experiment are verified by visual effects and objective evaluation. The proposed algorithm can preserve the weak edge and contour information while suppressing the noise of the sonar image. It has better peak signal-to-noise ratio, signal-to-noise ratio and Structural similarity.

关键词： Sonar wavelet coefficients wavelet domain Hidden Markov models image enhancement Feature extraction wavelet analysis

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