Balancing interpixel cross talk and detector noise to optimize areal density in holographic storage systems

We investigate the effects of interpixel cross talk and detector noise on the areal storage density of holographic data storage. A numerical simulation is used to obtain the bit-error rate (BER) as a function of hologram aperture, pixel fill factors, and additive Gaussian intensity noise. We consider the effect of interpixel cross talk at an output pixel from all possible configurations of its 12 closest-neighbor pixels. Experimental verification of this simulation procedure is shown for several fill-factor combinations. The simulation results show that areal density is maximized when the aperture coincides with the zero order of the spatial light modulator (SLM) (Nyquist sampling condition) and the CCD fill factor is large. Additional numerical analysis including finite SLM contrast and fixed-pattern noise show that, if the fixed-pattern noise reaches 6% of the mean signal level, the SLM contrast has to be larger than 6:1 to maintain high areal density. We also investigate the improvement of areal density when error-prone pixel combinations are forbidden by using coding schemes. A trade-off between an increase in areal density and the redundancy of a coding scheme that avoids isolated-on pixels occurs at a code rate of approximately 83%.     

Three-dimensional holographic disks

We describe optical disks that store data holographically in three dimensions by using either angle multiplexing or wavelength multiplexing. Data are stored and retrieved in parallel blocks or pages, and each page consists of approximately 10(6) bits. The storage capacity of such disks is derived as a function of disk thickness, pixel size, page size, and scanning parameters. The optimum storage density is approximately 120 bits/μm(2).     

Detection signal-to-noise ratio versus bit cell aspect ratio athigh areal densities

As areal density in hard drives increases, the bit aspect ratio (BAR) becomes an increasingly critical design issue. In this paper, we use the detection signal-to-noise ratio (SNR) as a system-level indicator to establish the relationship between the optimal BAR and all major recording system parameters that relate to the head/medium combination and servo as well as the read channel. We address practical and fundamental issues including thermal stability, medium and additive system noise, and equalization and track misregistration. The results of our analysis generally agree with the recent consensus to move toward lower BARs but also caution that the optimal BAR is a strong function of the servo capability. The results of our BAR analysis also indicate that at high areal densities, the ratio of PW50 to the bit cell is considerably smaller than found in today's drives     

Sparse modulation coding for increased capacity in volume holographic storage

In page-oriented memories, data pages commonly consist of comparable numbers of on and off pixels. Data-page sparsity is defined by reduction of the number of on pixels per page, leading to an increased diffracted power into each pixel. When page retrieval is dominated by a fixed noise floor, the number of pages in the memory is limited by the pixel diffraction efficiency. Sparsity increases the number of storable pages while reducing the amount of user information per page. A detailed analysis of sparsity in volume holographic memories shows that the total memory capacity can be increased by 15% by use of data pages that contain on average 25% on pixels. Sparsity also helps to reduce the effects of interpixel cross talk by strongly reducing the probability that worst-case pixel patterns (e.g., blocks of on pixels with a center off pixel) will occur in the data page. Enumeration block coding techniques provide construction of sparse-data pages with minimal overhead. In addition, enumeration coding offers maximum-likelihood detection with low encoding-decoding latency. We discuss the theoretical advantages of data-page sparsity. We also present experimental results that demonstrate the proposed capacity gain. The experiment verifies that it is practical to construct and use sparse-data pages that result in an overall user capacity gain of 16% subject to a page retrieval bit-error rate of 10(-4).     

基于GA-BP算法噪声检测的椒盐噪声滤波算法

基于噪声检测的中值滤波器已广泛用于消除图像中的椒盐噪声,然而在高噪声密度情况下,对噪声像素的定位不准确很容易造成图像边缘的模糊.本文提出了一种基于GA-BP的椒盐噪声滤波算法,克服了这一缺陷.算法首先用遗传算法优化的BP网络对图像中的噪声像素定位,然后引入保边函数和PRP算法求目标函数的极值进而实现图像的去噪处理.实验...     

Scene-based method for spatial misregistration detection in hyperspectral imagery

Hyperspectral imaging (HSI) sensors suffer from spatial misregistration, an artifact that prevents the accurate acquisition of the spectra. Physical considerations let us assume that the influence of the spatial misregistration on the acquired data depends both on the wavelength and on the across-track position. A scene-based method, based on edge detection, is therefore proposed. Such a procedure measures the variation on the spatial location of an edge between its various monochromatic projections, giving an estimation for spatial misregistration, and also allowing identification of misalignments. The method has been applied to several hyperspectral sensors, either prism, or grating-based designs. The results confirm the dependence assumptions on lambda and theta, spectral wavelength and across-track pixel, respectively. Suggestions are also given to correct for spatial misregistration.     

Two bit correlation-an adaptive time delay estimation

Time delay estimation is a very important operation in ultrasound time-domain flow mapping and correction of phase aberration of an array transducer. As the interest increases in the application of one and a half-dimensional (1.5-D) and two-dimensional (2-D) array transducers to improving image quality and three-dimensional (3-D) imaging, the need of simple, fast, and sufficiently accurate algorithms for real-time time delay estimation becomes exceedingly crucial. In this paper, we present an adaptive time-delay estimation algorithm which minimizes the problem of noise sensitivity associated with the one bit correlation while retaining simplicity in implementation. This algorithm converts each sample datum into a two bit representation including the sign of the sample and an adaptively selected threshold. A bit pattern correlation operation is applied to find the time delay between two engaged signals. By using the criterion of misregistration as an indicator, we are able to show that the proposed algorithm is better than one bit correlation in susceptibility to noise level. Analytical results show that the improvement in reducing misregistration of the two bit correlation over its counterpart is consistent over a wide range of noise level. This is achieved by an adaptive adjustment of the threshold to accommodate signal corruption due to noise. The analytical results are corroborated by results from simulating the blood as a random distribution of red blood cells. Finally, we also present a memory-based architecture to implement the two bit correlation algorithm whose computation time does not depend upon the time delay of the signals to be correlated     

TMR and squeeze at gigabit areal densities

The track misregistration (TMR) required to achieve gigabit areal densities is calculated for a set of components based on the average bit error rate for a file. The average error rate is a statistical average, based on the TMR of the file, of the on-track and off-track error rate. The on-track and off-track error rates are dependent on squeeze from adjacent tracks. In this analysis, the average error rate is calculated using measured error rate profiles of the center track. For a file average soft error rate of 1×10^-6, the results show, for a particular head/disk combination designed for gigabit recording and operating at a linear density of 158 kbpi, that a track pitch of 4.0 μm (3.35 ktpi) can be achieved with a TMR of 0.635 μm. Obtaining this TMR value in a file is one of the challenges to recording of 1 Gb/in² in magnetic storage products     

Image oversampling for page-oriented optical data storage

Page-oriented data storage systems incorporate optical detector arrays [such as complementary metal-oxide semiconductor (CMOS) arrays] in order to read data images. For laboratory demonstrations the detector array is typically pixel matched to the data image [Opt. Lett. 22, 1509 (1997)]. This approach requires exceedingly high-performance optics and mechanics for the simultaneous alignment of each data-bearing pixel image to a detector element to be achieved. Systems intended for commercialization are designed with detector arrays that spatially sample the image at or above the Nyquist rate in order to read poorly aligned and distorted images [S. Redfield, Holographic Data Storage (Springer-Verlag, 2000), pp. 347-349]. However, for data page sizes exceeding a megapixel this approach becomes prohibitive in terms of detector bandwidth, size, power, cost, and processing requirements. We have instead developed a sub-Nyquist oversampling methodology that can recover arbitrarily aligned and distorted megapixel data page images with pixel-matched fidelity by using fewer than double the number of detector pixels. Features required for practicable implementation are described, including fiducials for alignment determination.     

Image restoration by adaptive-neighborhood noise subtraction

A new algorithm for image restoration in the presence of additive white Gaussian noise is presented. This algorithm is based on a new, adaptive method to estimate the additive noise. The basic idea in this technique is to identify uniform structures or objects in the image by use of an adaptive neighborhood and to estimate the noise and the signal content in these areas separately. The noise is then subtracted selectively from the seed pixel of the adaptive neighborhood, and the process is repeated at every pixel in the image. The algorithm is compared with the adaptive two-dimensional least-mean-squares and the adaptive rectangular-window least-mean-squares algorithms for noise suppression. The results from the application of these algorithms to synthesized images and natural scenes are presented along with mean-squared-error measures. The new algorithm performs better than the other two methods both in terms of visual presentation and mean-squared error.     

Two-Color Holographic Recording Scheme Allowing Nonvolatile Reading in Mn:YAlO(3)

We propose and experimentally realize the recording of two-color holographic gratings in Mn:YAlO(3), a potential material for holographic data storage. This type of recording allows for nonvolatile retrieval of recorded information at the recording wavelength. We demonstrate two-color recording and readout of a 256 x 256 pixel page using red and green laser beams with a bit error rate of 6 x 10(-7).     

Data-Aided Timing Recovery for Recording Channels With Data-Dependent Noise

In high-density data storage systems, noise becomes highly correlated and data dependent as a result of media noise, channel nonlinearities, and front-end filters. In such environments, conventional timing recovery schemes will exhibit large residual timing jitter and, especially, data-dependent timing jitter. This paper presents a new data-aided timing recovery algorithm for data storage systems with data-dependent noise. We derive a maximum-likelihood timing recovery scheme based on a data-dependent Gauss-Markov model of the noise. The timing recovery algorithm incorporates data-dependent noise prediction parameters in the form of linear prediction filters and prediction error variances. Moreover, because noise can be nonstationary in practice, we propose an adaptive algorithm to estimate and track the noise prediction parameters. Simulation results, for an idealized optical storage channel incorporating a simple model of media noise, illustrate the merits of our algorithm     

Reversible Data Hiding in Encrypted Images Based on Prediction and Adaptive Classification Scrambling

Reversible data hiding in encrypted images (RDH-EI) technology is widely used in cloud storage for image privacy protection. In order to improve the embedding capacity of the RDH-EI algorithm and the security of the encrypted images, we proposed a reversible data hiding algorithm for encrypted images based on prediction and adaptive classification scrambling. First, the prediction error image is obtained by a novel prediction method before encryption. Then, the image pixel values are divided into two categories by the threshold range, which is selected adaptively according to the image content. Multiple high-significant bits of pixels within the threshold range are used for embedding data and pixel values outside the threshold range remain unchanged. The optimal threshold selected adaptively ensures the maximum embedding capacity of the algorithm. Moreover, the security of encrypted images can be improved by the combination of XOR encryption and classification scrambling encryption since the embedded data is independent of the pixel position. Experiment results demonstrate that the proposed method has higher embedding capacity compared with the current state-ofthe-art methods for images with different texture complexity.     

Nanodomain manipulation for ultrahigh density ferroelectric data storage

Nanosized inverted domain dots in ferroelectric materials have potential application in ultrahigh density rewritable data storage systems. Herein, a data storage system is presented based on scanning non-linear dielectric microscopy and a thin film of ferroelectric single-crystal lithium tantalite. Through domain engineering, we succeeded in forming our smallest artificial nanodomain single dot at 5.1?nm diameter and an artificial nanodomain dot array with a memory density of 10.1?Tbit?inch(-2) and a bit spacing of 8.0?nm, representing the highest memory density for rewritable data storage reported to date. Subnanosecond (500?ps) domain switching speed has also been achieved. Next, actual information storage with a low bit error and high memory density was performed. A bit error ratio of less than 1 × 10(-4) was achieved at an areal density of 258?Gbit?inch(-2). Moreover, actual information storage is demonstrated at a density of 1?Tbit?inch(-2).     

Recording on Bit-Patterned Media at Densities of 1 Tb/in$^2$and Beyond

We present a comprehensive analysis of the areal density potential of a bit-patterned media recording. The recording performance is dominated by written-in errors rather than traditional signal-to-noise considerations. Written-in errors are caused by statistical fluctuations of the magnetic properties and the locations of the individual dots. The highest areal densities are obtained with a combination of a pole head, a soft magnetic underlayer, and a storage medium of the composite type. Areal density scenarios of up to 5 Tb/in$^2$are analyzed.     

A measurement of signal-to-noise ratio versus trackwidth from 128 µm to 4 µm

Bulk-erased tape noise will vary as the square root of the reproduce head trackwidth if the noise signal is uncorrelated across the track. Recent models of erased noise involve clusters of interacting particles that could be as large as a few microns. As the trackwidth (TW) approaches the cluster size, the noise should become correlated across the track and the tape-noise-limited signal-to-noise ratio (SNR) should become constant as TW is further reduced. A check of this idea using inductive heads is impractical. Magnetoresistive (MR) heads have very high signal and low noise and so are well suited for this task, but precautions must be taken to minimize thermal and Barkhausen noise. A multichannel MR head having TW from 128 μM to 4 μM was built to explore the areal reproduce density limits of MR heads and measure the bulk-erased SNR versus TW for 3M 5198 tape. Tape-noise-limited performance was achieved with the narrowest 4μM TW channel at a wavelength as short as 1μM. A wideband-equalized SNR of 20 dB was demonstrated with this channel at a wavelength of 1.27 μm or 40 kilo flux changes per inch (40 kFCI), at a tape speed of 38.2 cm/sec. With a 100% guard band, or an 8-μm track-to-track pitch, this corresponds to the very high areal storage density of 127 MFC/in². The SNR was found to vary assqrt{TW}down to TW = 4 μm, which indicates that the expected particle cluster size must be smaller than 4 μm in the crosstrack direction.     

3 Gb/in2 recording demonstration with dual element headsand thin film disks

We have successfully demonstrated magnetic recording at an areal density of 3 Gb/in² with narrow track inductive-write MR-read dual element heads on low noise Co alloy thin film disks. In this demonstration, the write head is a ten turn thin film inductive head with thick and narrow P2 pole-tips. The read head is a shielded ~1 μm trackwidth MR sensor soft-film biased in the read region for linearization and exchange-biased at the tail regions for magnetic stabilization. During recording tests, the heads were flown over low noise Co-alloy media at a clearance similar to that in the previous 1 Gb/in² recording experiment. Results showed good writability from the narrow track write head in terms of overwrite and hard transition shift. Readback yields symmetrical signals as large as 600 μV (p-p) and rolloff measurements showed 50% densities as high as 5000 fc/mm. Track profile and microtrack profile measurements showed the write and read trackwidths to be ~1.4 μm and ~1.1 μm respectively, with tight side-writing and side-reading characteristics. An overall assessment of the parametric recording results suggested areal density feasibility up to as high as 3 Gb/in². This projection was confirmed by error rate performance testing using a PRML channel with a digital filter and write precompensation. At a data rate of 4-5 Mb/s and at very low ontrack error, a linear density as high as 185 Kbpi and an optimized track pitch as narrow as 1.5 μm were achieved, corresponding to an areal recording density of ~3.1 Gb/in²     

提高Hartmann波前传感器质心探测精度的阈值方法

详细地讨论了Ｈａｒｔｍａｎｎ波前传感器质探测的误差来源。主要讨论了光量子起伏、ＣＣＤ的背影电子噪声引起的质心探测误差，并对采样阈值对Ｈａｒｔｍａｎｎ波前传感器质心探测精度的影响进行了分析。本文对Ｈａｒｔｍａｎｎ波前传器的经设计以及实际操作提供了一定的理论依据。     

Nanoscale ferroelectric information storage based on scanning nonlinear dielectric microscopy

An investigation of ultrahigh-density ferroelectric data storage based on scanning nonlinear dielectric microscopy (SNDM) is described. For the purpose of obtaining fundamental knowledge on high-density ferroelectric data storage, several experiments on nanodomain formation in a lithium tantalate (LiTaO3) single crystal were conducted. Through domain engineering, a domain dot array with an areal density of 1.5 Tbit/inch2 was formed on congruent LiTaO3 (CLT). Sub-nanosecond (500 psec) domain switching speed also has been achieved. Next, actual information storage is demonstrated at a density of 1 Tbit/inch2. Finally, it is described that application of a very small dc offset voltage is very effective in accelerating the domain switching speed and in stabilizing the reversed nano-domain dots. Applying this offset application technique, we formed a smallest artificial nano-domain single dot of 5.1 nm in diameter and artificial nano-domain dot-array with a memory density of 10.1 Tbit/inch2 and a bit spacing of 8.0 nm, representing the highest memory density for rewritable data storage reported to date.     

噪声概率快速估计的自适应椒盐噪声消除算法

提出一种可识别噪声概率自动调节滤波窗口的自适应椒盐噪声消除算法。对非理想椒盐噪声污染图像随机区域进行变窗口中值滤波,将结果与滤波前比对获得噪声点数,滤波区域即按此点数排序。然后取每种滤波窗口下的中间三组数据,该数据平均加权获取图像噪声概率初估计,对初估计平均加权即得图像噪声概率。滤波前首先采用阈值法排除明显噪声点,剩余像素中再以离窗口中心像素距离平方的倒数为权值估计中心像素。最后由噪声概率按照T-S模糊规则对不同模型的输出估计值进行融合。实验证明,与传统中值滤波等算法相比,该算法具有噪声自动估计和自适应窗口调节能力,滤波后标准均方差可减少20%以上,速度可提高一倍多。