一种解决版权问题的数字水印方案

大部分水印技术侧重于水印的不可见性和稳健性,而版权保护问题并未得到真正解决。该文提出的数字水印方案可以有效地解决这一问题。通过一种新颖的水印构造方法,有效地消除了在解决版权问题中对使用原始图像的限制。盲与非盲水印检测时水印的不可见性和稳健性均得到很大提高。实验结果证明该数字水印方案对于版权攻击是有效的,对各种失真都具有较强的稳健性。     

数字水印技术在数字作品内容认证方面的应用

数字水印技术主要用于数字作品的版权保护、数字信息的真伪鉴别和保密通讯三大领域。电子文件的版权保护、安全性等问题越来越重要，这些需求都极大地促进了数字水印技术的发展。数字水印在帮助保持和验证数字作品的完整性上的应用具有独特的优势和广阔的前景。     

Novel wavelet-based QIM data hiding technique for tamper detection and correction of digital images

This paper proposes a tamper detection and correction technique using semi-fragile data hiding that aims to achieve high perceptual quality of images at the user-end even after malicious modifications. A binary signature and an image digest are embedded by modulating integer wavelet coefficients using dither modulation based quantization index modulation. Half-toning technique is used to obtain image digest from the low-resolution version of the host image itself. Decoder extracts the binary signature from the watermarked image for tamper detection, while the extracted image digest is used to correct the tamper region. Unlike previously proposed techniques, this novel approach distinguishes malicious changes from various common image processing operations more efficiently and also correct tapered regions effectively. Experimental results show that the proposed technique provides a superior performance in terms of probability of miss and false alarm as well as in tamper correction, compared to several existing semi-fragile watermarking techniques.     

A precise sensor fault detection technique using statistical techniques for wireless body area networks

One of the major challenges in wireless body area networks (WBANs) is sensor fault detection. This paper reports a method for the precise identification of faulty sensors, which should help users identify true medical conditions and reduce the rate of false alarms, thereby improving the quality of services offered by WBANs. The proposed sensor fault detection (SFD) algorithm is based on Pearson correlation coefficients and simple statistical methods. The proposed method identifies strongly correlated parameters using Pearson correlation coefficients, and the proposed SFD algorithm detects faulty sensors. We validated the proposed SFD algorithm using two datasets from the Multiparameter Intelligent Monitoring in Intensive Care database and compared the results to those of existing methods. The time complexity of the proposed algorithm was also compared to that of existing methods. The proposed algorithm achieved high detection rates and low false alarm rates with accuracies of 97.23% and 93.99% for Dataset 1 and Dataset 2, respectively.     

A visual model weighted cosine transform for hiding watermark in images

Watermarking is a technique for labeling digital pictures by hiding secret information into images. Watermark embedding is a method to discourage unauthorized copying and identify the owner or distributor of digital data. In this paper, a new method is proposed. The watermark is processed as a visually recognizable pattern-binary image, which includes more information than the traditional symbol or ID number and is "extracted" instead of only "detected" to characterize the owner. The watermark is hidden in the host image by selectively modifying the middle-frequency part of the host image in conjunction with the human visual system(HVS) and the image discrete cosine transform(DCT). The experimental results show that this method can survive image cropping and image compression, and get better results, this is also a prospective method.     

A distributed source coding technique for correlated images using turbo-codes

The Slepian-Wolf (1973) theorem states that the output of two correlated sources can be compressed to the same extent without loss, whether they communicate with each other or not, provided that decompression takes place at a joint decoder. We present a distributed source coding scheme for correlated images which uses modulo encoding of pixel values and encoding (compression) of the resulting symbols with binary and nonbinary turbo-codes, so that larger rate savings than using modulo encoding. alone are achieved, practically without loss.     

A novel digital compensation technique for current bias without additional power consumption

A new digital compensation technique is proposed for current reference. The current variations induced by deviations of temperature and process are calibrated through a digital method. The circuit structure is simplified, and the problem of instability in conventional analog current bias can be overcome since the digital part cut off the closed compensation loop. Designed with 0.18 μm CMOS technology, the output current can be calibrated to 100 μA with a maximum error of ±0.3 μA under all the process corners, no matter how the temperature changes in an ultra-wide range of ?116 to 160 °C. In addition, the current precision can be maintained as the load voltage varies in the range of 0.31–1.04 V, and the load sensitivity is about 8,000 ppm/V. The digital part can be shut down after the calibration phase, so no additional power will be consumed except the bias itself.     

A thinning transform for digital images

Given an elongated object in a digital image, a thinning transform is described to simultaneously calculate the coordinates of its medial line elements and a value for these elements equal to the width of the object at the element's coordinates. The transform is being used in the area of quantitative fractography in photo-micrographs of rock samples.     

一种基于图像融合的数字水印方案

数字水印是一种新型的多媒体信息版权保护技术，它是在多媒体信息中嵌入标志版权信息的不可感知且难以去除的水印信息，通过检测水印信息来进行版权保护及盗版跟踪，从而有效地弥补了数字加密技术的不足之处。提出了一种具有良好鲁棒性的数字水印方案。由于该方案利用人眼视觉系统把数字水印嵌入到图像的视觉重要区域中，对水印的破坏将会非常困难。     

基于相位分析的散斑图像位移测量算法

通过对数字散斑图像位移测量方法和激光散斑图像特点的研究,提出了一种利用数字散斑图像进行位移测量的新方法:同频率相位比较法.该方法把移动前后的激光散斑图像像素分别在X、Y方向上叠加,对叠加后的一维序列进行频谱分析,找出同一频率的信号的存前后两幅散斑中的相位偏移,然后通过统计分析求解激光散斑图像的位移.大量实验证明,上述算法可行,不使用插值法即可求解亚像素级位移,并能大幅度提高位移测量速度.     

A robust method for fingerprinting digital images

In this paper, a method to fingerprint digital images is proposed, and different watermarked copies with different identification string are made. After determining the number of the customers and the length of the watermark string, this method chooses some values inside the digital image using a characteristic function, and adds watermarks to these values in a way that can protect the product against the attacks happened by comparing two fingerprinted copies. The watermarks are a string of binary numbers -1s and 1s. Every customer will be distinguished by a series of 1s and -1s generated by a pseudo-random generator. The owner of the image can determine the number of customers and the length of the string as well as this method will add another watermarking values to watermark string to protect the product.     

Blind method for rescaling detection and rescale factor estimation in digital images using periodic properties of interpolation

Availability of the powerful image editing softwares and advancement in digital cameras has given rise to large amount of manipulated images without any traces of tampering, generating a great demand for automatic forgery detection algorithms in order to determine its authenticity. When altering an image like copy–paste or splicing to conceal traces of tampering, it is often necessary to resize the pasted portion of the image. The resampling operation may highly likely disturb the underlying inconsistency of the pasted portion that can be used to detect the forgery. In this paper, an algorithm is presented that blindly detects global rescaling operation and estimate the rescaling factor based on the autocovariance sequence of zero-crossings of second difference of the tampered image. Experimental results using UCID and USC-SIPI database show the validity of the algorithm under different interpolation schemes. The technique is robust and successfully detects rescaling operation for images that have been subjected to various forms of attacks like JPEG compression and arbitrary cropping. As expected, some degradation in detection accuracy is observed as the JPEG quality factor decreased.     

A method for digital processing of bitmap images

A method for processing of graphical information is proposed. The method makes it possible to code contour images with the use of complex numbers unambiguously defined by the image shape. Mapping of a noise bitmap image onto the complex plane is studied. The possibility of solving such recognition problems as object identification and determination of the orientation of a figure in a plane is demonstrated.     

Noise equalization for detection of microcalcification clusters in direct digital mammogram images

Equalizing image noise is shown to be an important step in the automatic detection of microcalcifications in digital mammography. This study extends a well established film-screen noise equalization scheme developed by Veldkamp et al. for application to full-field digital mammogram (FFDM) images. A simple noise model is determined based on the assumption that quantum noise is dominant in direct digital X-ray imaging. Estimation of the noise as a function of the gray level is improved by calculating the noise statistics using a truncated distribution method. Experimental support for the quantum noise assumption is presented for a set of step wedge phantom images. Performance of the noise equalization technique is also tested as a preprocessing stage to a microcalcification detection scheme. It is shown that the square root model based approach which FFDM allows leads to a robust estimation of the high frequency image noise. This provides better microcalcification detection performance when compared to the film-screen noise equalization method developed by Veldkamp. Substantially better results are obtained than when noise equalization is omitted. A database of 124 direct digital mammogram images containing 28 microcalcification clusters was used for evaluation of the method.     

Noise reduction using multiscale bilateral decomposition for digital color images

In this paper, we propose a noise reduction algorithm for digital color images using a nonlinear image decomposition approach. Most existing noise reduction methods do not adequately consider spatial correlation of color noise in digital color images. Color noise components in color images captured by digital cameras are observed as irregular grains with various sizes and shapes, which are spatially randomly distributed. We use a modified multiscale bilateral decomposition to effectively separate signal and mixed-type noise components, in which a noisy input image is decomposed into a base layer and several detail layers. A base layer contains strong edges, and most of noise components are contained in detail layers. Noise components in detail layers are reduced by an adaptive thresholding function. We obtain a denoised image by combining a base layer and noise-reduced detail layers. Experimental results show the effectiveness of the proposed algorithm, in terms of both the peak signal-to-noise ratio and visual quality.     

A low-power direct digital synthesizer using a self-adjustingphase-interpolation technique

A complete direct digital synthesizer (DDS) using a self-adjusting phase-interpolation technique is fabricated using 0.35-μm CMOS process technology. A self-adjusting delay generator reduces the periodic jitter in the most significant bit (MSB) of the accumulator in this DDS. To improve the spectral performance, a method of spurious signal reduction that uses offset current sources (OCSs) is newly adopted in the delay generator. Test results confirm that the delay generator produces highly accurate delay timing without the need to adjust circuit constants. The measured spurious free dynamic range (SFDR) is 62 dBc for a dc to 10-MHz output and the power consumption of the complete DDS is 39.2 mW at a 100-MHz clock rate     

A deterministic digital calibration technique for pipelined ADCs using a non-nested algorithm

Analog Integrated Circuits and Signal Processing - This paper proposes a novel deterministic technique to digitally calibrate 1.5-bits/stage and 1-bit/stage pipelined as well as algorithmic...     

Partition-based vector filtering technique for suppression of noise in digital color images.

A partition-based adaptive vector filter is proposed for the restoration of corrupted digital color images. The novelty of the filter lies in its unique three-stage adaptive estimation. The local image structure is first estimated by a series of center-weighted reference filters. Then the distances between the observed central pixel and estimated references are utilized to classify the local inputs into one of preset structure partition cells. Finally, a weighted filtering operation, indexed by the partition cell, is applied to the estimated references in order to restore the central pixel value. The weighted filtering operation is optimized off-line for each partition cell to achieve the best tradeoff between noise suppression and structure preservation. Recursive filtering operation and recursive weight training are also investigated to further boost the restoration performance. The proposed filter has demonstrated satisfactory results in suppressing many distinct types of noise in natural color images. Noticeable performance gains are demonstrated over other prior-art methods in terms of standard objective measurements, the visual image quality and the computational complexity.     

A statistical and geometrical edge detector for SAR images

A constant-false-alarm-rate (CFAR) edge detector based on the ratio between pixel values is described. The probability distribution of the image obtained by applying the edge detector is derived. Hence, the decision threshold can be theoretically determined for a given probability of false alarm as a function of the number of looks of the image under study and the size of the processing neighborhood. For a better and finer detection, the edge detector operates along the four usual directions over windows of increasing sizes. A test performed, for a given direction, on a radar image of an agricultural scene shows good agreement with the theoretical study. The operator is compared with the CFAR edge detectors suitable for radar images     

以IMEI/IMSI为水印的手机图像数字水印算法的实现

随着网络、无线通信和摄像机便携设备的快速发展,带来了数字图像很容易散布、复制和修改.针对此类问题,提出一种以手机IMEI/IMSI码为水印信息并嵌入到手机图像的数字水印算法,从而达到手机图像的版权保护.首先获取手机IMEI/IMSI,使用BCD编码将其转换成二进制向量,再使用BCH编码转换成64 ×64水印位图作为水印信息;然后采用离散余弦变换、离散小波变换和奇异值分解结合的算法将水印信息嵌入到手机图像;最后提取水印信息来获取用户的手机信息.实验表明该算法能够实现盲提取,具有良好的不可见性、鲁棒性,能够抵抗一定的压缩、噪声等攻击.