Image encryption based on the multiple-order discrete fractional cosine transform

A novel scheme for image encryption based-on the multiple-order discrete fractional cosine transform (MODFrCT) is proposed. The DFrCT has a similar relationship with the discrete fractional Fourier transform (DFrFT). Not only has the DFrCT many useful properties similar to the conventional discrete cosine transform, but it also has another property, namely its fraction, or its transform order. The image to be encrypted is transformed with the multiple-order DFrCT using a random row cipher key vector and a random column key vector successively, and the corresponding cipher key vectors of decryption are also very sensitive. The transmission of the encrypted image with the algorithm of the multiple-order DFrCT is faster due to its reality. The digital simulation results proved the validity and safety of this algorithm.     

Fingerprint image enhancement using multi-scale DDFB based diffusion filters and modified Hong filters

The main task of a fingerprint image enhancement is to enhance the image in such a way that it not only remove the noise but also enhance the reliable minutiae points. For this purpose, in this paper we propose a multi-scale decimation-free directional filter bank method for reliable orientation estimation. This reliable orientation is used in coherence enhancement diffusion and in Gabor filter based enhancement, which overcomes the drawbacks of these two methods. Experimental results show that the proposed method not only enhances the images but also facilitates the minutiae algorithm, by enhancing the true minutiae points.     

An adaptive speech enhancement method for siren noise cancellation

Siren noises usually severely disturb the intelligibility of voice communication inside the cabs of police, paramedic and fire vehicles. It is often desired that such unwanted noise can be removed from the speech signal. In this paper, a new method is proposed to adaptively cancel siren noises and enhance speech signals. Based on the characteristics of siren noises, an anti-speech filter and a time delayer are employed in the single and dual channel noise cancellation systems to reduce the siren noises. Experiment results demonstrate that the effectiveness of the proposed method for canceling the siren noises and the performance of the enhanced speech signal is satisfying.     

Speech enhancement in dual-microphone mobile phones using Kalman filter

In this paper, a dual-microphone speech enhancement algorithm for the mobile phones is proposed. The adopted method exploits the coherence function algorithm and the Kalman filter. This algorithm has a simple implementation that does not need a prediction of interfering signals statistics. In addition, this algorithm can be used in small devices with so closely distance between the two microphones. Moreover, the use of such algorithm allows reducing multiple noise sources at many azimuths positions. Finally, the new algorithm proves its performances referring to the perceptual evaluation of speech quality and the time domain waveforms.     

基于数字全息与小波变换的图像数字水印技术

提出一种以数字全息和小波变换为基础的数字水印技术,实现在原始图像中嵌入数字全息水印。首先通过傅里叶变换方法将待隐藏的图像制成数字全息水印图,接着将数字全息水印图和原始图像都分为四个子块,并对原始图像子块进行小波分解,最后将数字全息图像子块嵌入到原始图像相应子块较大的小波系数中。实验仿真结果证明了该水印技术对图像剪切和图像有损压缩有较好的稳定性。     

Speech enhancement using linearly constrained adaptive constant directivity beam-formers

This paper aims to extend previous work on constant directivity beam-formers (CDBs), for the case of multiple desired speech sources, by designing a linearly constrained adaptive CDB (LCA-CDB) which preserves the beam-pattern in multiple look directions. Also, the proposed LCA-CDB, adaptively, minimizes the transient noise power in the output of the beam-former, and furthermore, produces some controlled nulls (controlled in both amplitude and angle) on the beam-pattern. This strengthens the system in removing permanent directional noises and producing a frequency-invariant beam-pattern with multiple main-lobes and controlled nulls in arbitrary frequency bands. Through simulating the system and the acoustical situations, the authors have tried to demonstrate the capability of the proposed method in enhancement of broadband and telephony speech in the presence of various noise sources (transient noise, permanent noise and uncorrelated white Gaussian noise). The simulation results obtained in this study confirm the efficiency of the proposed method in suppression of environmental noises.     

不对称离散分数傅里叶变换实现数字图像的加密变换

利用不对称分数傅里叶变换的特性,提出了一种图像加密变换的新方法。对图像的x,y方向分别实施不同级次的一维分数傅里叶变换,得到加密图像。解密方法就是对变换后的图像实施对应级次的分数傅里叶逆变换,只有当x,y方向的逆变换级次分别与原变换级次都相同或者满足周期条件时,才能恢复原图像。加密变换有效地提高了图像加密和防伪力度。数值计算验证了方法的正确性和可行性。     

改进的正交匹配追踪的语音增强算法*

为了提高传统正交匹配追踪（Orthogonal Matching Pursuit,OMP ）算法的语音增强性能和运算速度,本研究基于稀疏编码理论,提出了一种改进的OMP算法的语音增强算法。其一,将K-奇异值分解（K-singular value decomposition,K-SVD）算法与OMP算法相结合,通过设置能量阈值的方法,提高OMP算法的语音增强性能;其二,通过改进传统OMP算法中信号稀疏逼近的计算方法,提高算法的运算速度。改进的OMP算法的语音增强算法与传统K-SVD语音增强算法相比,采用PESQ评价增强语音的质量,NCM评价语音的可懂度。在NCM的值基本保持不变的情况下,PESQ的值平均提高约12.47%,取得了更好的增强效果。取得了更好的增强效果。改进的OMP算法的运算速度与传统OMP算法相比提高近一倍。     

Double-image encryption based on discrete fractional random transform and chaotic maps

A novel double-image encryption algorithm is proposed, based on discrete fractional random transform and chaotic maps. The random matrices used in the discrete fractional random transform are generated by using a chaotic map. One of the two original images is scrambled by using another chaotic map, and then encoded into the phase of a complex matrix with the other original image as its amplitude. Then this complex matrix is encrypted by the discrete fractional random transform. By applying the correct keys which consist of initial values, control parameters, and truncated positions of the chaotic maps, and fractional orders, the two original images can be recovered without cross-talk. Numerical simulation has been performed to test the validity and the security of the proposed encryption algorithm. Encrypting two images together by this algorithm creates only one encrypted image, whereas other single-image encryption methods create two encrypted images. Furthermore, this algorithm requires neither the use of phase keys nor the use of matrix keys. In this sense, this algorithm can raise the efficiency when encrypting, storing or transmitting.     

基于自适应正交有限脊波变换的图像编码算法

在有限脊波变换的基础上,根据对图像有限Radon变换系数的分析,提出了一种自适应的正交有限脊波变换。此变换根据特别设计的代价函数,可自适应地为每列有限Radon变换系数选择最优的正交变换形式,从而可高效地分析图像中的直线奇异。讨论了此变换在图像编码领域中的应用,通过对零树编码算法SPIHT进行改进,实现了图像自适应正交有限脊波变换系数的渐进编码。实验结果表明,对富含直线边缘的图像来说,与小波图像编码算法相比,该算法获得了较高的边缘重建质量。     

Image sharing scheme based on discrete fractional random transform

We present a novel image sharing algorithm based on the discrete fractional random transform (DFRNT). The secret image is shared into several shadow images in the DFRNT domain together with some noise images as the encryption keys to increase the security. The decryption only requires a part of shadow images and therefore is independent of those noise images. The (t,n) threshold sharing scheme can be implemented completely by the proposed algorithm. The numerical simulations have demonstrated the effectiveness of this image sharing scheme.     

Copyright protection in digital museum based on digital holography and discrete wavelet transform

A new method to protect the copyright of digital museum based on digital holography is proposed. The Fresnel hologram of watermark image is embedded in the object to be protected through discrete wavelet transform （DWT）. After the watermark detection, the copyright information appears in the reconstructed hologram. With the higher redundancy feature in the hologram, the proposed technique can actually survive several kinds of image processing. Experimental results prove that the presented method has good robustness in image protection.     

A wavelet-based forward BSS algorithm for acoustic noise reduction and speech enhancement

In this paper, we address the problem of noise reduction and speech enhancement by adaptive filtering algorithm. Recently, the well known forward blind source separation (FBSS) structure has been largely studied and intensively used to reduce acoustic noise components and to enhance speech signal. The FBSS structure is often combined with adaptive algorithms to accelerate the adaptation of the cross-filters, and to improve noise suppression at the output. In this paper, we propose to use a wavelet transform decomposition in the FBSS structure by using a two-channel forward wavelet symmetric adaptive decorrelating (WFSAD) algorithm. The proposed WFSAD algorithm provides a better compromise between time and frequency resolution and improves robustness of the noise reduction process when compared with the classical two-channel forward symmetric adaptive decorrelating (FSAD) algorithm. Simulation results prove the efficiency of the proposed WFBSS algorithm in comparison with conventional ones in terms of several objective and subjective criteria.     

Speech enhancement method based on low-rank approximation in a reproducing kernel Hilbert space

Speech signal is corrupted unavoidably by noisy environment in subway, factory, and restaurant or speech from other speakers in speech communication. Speech enhancement methods have been widely studied to minimize noise influence in different linear transform domain, such as discrete Fourier transform domain, Karhunen-Loeve transform domain or discrete cosine transform domain. Kernel method as a nonlinear transform has received a lot of interest recently and is commonly used in many applications including audio signal processing. However this kind of method typically suffers from the computational complexity. In this paper, we propose a speech enhancement algorithm using low-rank approximation in a reproducing kernel Hilbert space to reduce storage space and running time with very little performance loss in the enhanced speech. We also analyze the root mean squared error bound between the enhanced vectors obtained by the approximation kernel matrix and the full kernel matrix. Simulations show that the proposed method can improve the computation speed of the algorithm with the approximate performance compared with that of the full kernel matrix.     

Hit-or-miss transform based infrared dim small target enhancement

To efficiently enhance a dim infrared small target embedded in heavy clutter, a hit-or-miss transform based method is proposed in this paper. First, the gray level hit-or-miss transform is given and discussed. Then, by analyzing the structuring elements used in the hit-or-miss transform following the purpose of infrared small target enhancement, a simple infrared small target enhancement method is proposed by using flat structuring elements and a threshold parameter. The threshold imports the properties of infrared small target into the gray level hit-or-miss transform, which improves the performance of the hit-or-miss transform for infrared small target enhancement. Experimental results on infrared dim small target images with different clutter backgrounds verified that the proposed method was efficient for infrared small target enhancement.     

Novel image encryption algorithm based on multiple-parameter discrete fractional random transform

A new method of digital image encryption is presented by utilizing a new multiple-parameter discrete fractional random transform. Image encryption and decryption are performed based on the index additivity and multiple parameters of the multiple-parameter fractional random transform. The plaintext and ciphertext are respectively in the spatial domain and in the fractional domain determined by the encryption keys. The proposed algorithm can resist statistic analyses effectively. The computer simulation results show that the proposed encryption algorithm is sensitive to the multiple keys, and that it has considerable robustness, noise immunity and security.     

结合幅度谱和功率谱字典的语音增强方法

从双路字典学习、噪声功率谱估计、语音幅度谱重构角度提出了一种改进的谱特征稀疏表示语音增强方法。在字典学习阶段,融合功率谱与幅度谱特征,采用区分性字典降低语音字典和噪声字典的相干性;在语音增强阶段,提出一种噪声功率谱估计方法对非平稳噪声进行跟踪估计;考虑到幅度谱和功率谱特征对不同噪声的适应程度不同,设计了语音重构权值表。对分别由幅度谱和功率谱恢复而来的两路信号进行自适应加权重构,结合相位补偿函数得到增强后的语音信号。实验结果表明,该方法在平稳、非平稳噪声环境下相比于单一谱特征的语音增强方法平均提高31.6%,改善了语音增强方法的性能。     

Blind image watermarking based on discrete fractional random transform and subsampling

This paper proposes a blind watermarking scheme based on discrete fractional random transform. The watermark information can be a binary sequence, a gray level image or a set of decimal fractions sampled from a given source signal. The host image is subsampled into four subimages, and the high correlations among their discrete fractional random transform coefficients are exploited for watermark embedding. Based on this self-reference strategy, the watermark can be extracted without the aid of the host image. As a fragile watermarking technique, our scheme can be used in tamper detection. Besides, it can be used in self-embedding for a large payload is provided. Meanwhile, security of the watermark is preserved due to the randomness of the discrete fractional random transform. Experimental results demonstrate the effectiveness of our scheme.     

Synthetic Aperture Radar image nonlinear enhancement algorithm based on NSCT transform

Due to the imaging mechanism, Synthetic Aperture Radar (SAR) images are susceptible to speckle noise, which affects radar image interpretation. So image denoising and enhancement are important topics of improving SAR image performance. A nonlinear image enhancement algorithm based on nonsubsampled contourlet transform (NSCT) is proposed in this paper. The image is decomposed into coefficients of different scales and directions through nonsubsampled contourlet transform. It is denoised by the threshold method of the multi-scale product of NSCT coefficients. Then thresholds of the nonlinear enhancement function are determined according to the coefficients of each scale. The two parameters of the function, among which one is used to control the range of enhancement and the other can determine the strength of enhancement, are obtained by solving nonlinear equations. The coefficients processed by the enhancement function are used to reconstruct the image. The simulation results on the Matlab platform show that the algorithm has a good effect of enhancing details of images and suppressing noise signals meanwhile.     

A speech enhancement method based on Kalman filtering

I.IntroductionKa1manfilteringisjustamethodtoestimatestatistica1lythestateoftheobservedsystemfromthecorruptedsigna1s,andthiskindofcstimationisarecurrcneeestimationbasedon1inear,nonbiasandminimumvariance.Moreover,Ka1manfilteringisapplicabletonon-sta-honarysignalsandtime-variantdynamicsystem.Therefore,Kalmanfilteringisveryapplica-bletoenhancingthespeechsigna1sthatarecorruptedbynoise.ThispaperreportStheconcretcmethodofenhanccmentofnoisyspccchanditscxperimentresults.Experimentsindicate:Afterthes…