Perception of temporally filtered X-ray fluoroscopy images

For noisy X-ray fluoroscopy image sequences we quantitatively evaluated image quality after digital temporal filtering to reduce noise. Using an experimental paradigm called a reference/test adaptive forced-choice method we compared detectability of stationary low-contrast disks in filtered and unfiltered, computer-generated image sequences. In the first experiment, a low-pass first-order recursive filter used in X-ray fluoroscopy was found to be much less effective at enhancing detectability than predicted from the reduction of display noise variance, a common measurement of filter effectiveness. Detectability was reasonably predicted by a nonprewhitening human-observer model (NPW-HVS) that included an independently determined human temporal-contrast-sensitivity function. In another experiment, designed to test models over a range of temporal frequencies, we used paired high-pass and low-pass temporal filters that both reduced noise variance by 25%. The high-pass filter was artificially applied to the noise only and greatly improved detectability, while the low-pass filter had little effect. The human-observer model quantitatively described the measurements, but classical prewhitening and nonprewhitening signal detectors did not. As compared to the nonprewhitening, spatio-temporal matched filter, human-observer efficiency was low and variable at 2.1%, 2.9%, and 0.06% for 60 frames of unfiltered low-pass and high-pass noise, respectively. As compared to this detector, humans were not very effective at combining information across frames. On the other hand, signal to noise ratios (SNR's) from the human-observer model were comparable to human performance, and efficiencies were reasonably constant at 40%, 52%, and 32%, respectively. We conclude that it is imperative to include human-observer models and experiments in the analysis of noise-reduction filtering of noisy image sequences, such as X-ray fluoroscopy.     

The Enriched Feature Enhancement Technique for Satellite Image Based on Transforms Using PCNN

The features of the satellite images can be improved by fusing or combining two images with complementary property. By fusing these two images the spatial property of the resultant image is improved. Satellite images are one of the agents that give the features of the earth’s surface. Processing these satellite images will provide more geographical information hidden in the images. This research paper have an detailed insight study of two types of the satellite images one is Panchromatic (PAN) and other Multispectral (MS). The PAN image with high spatial resolution and MS image with spectral resolution are fused to get better resultant output. For fusion process Nonsubsampled Contour let Transform is used to decompose the images into low and high frequency values. Pulse Coupled Neural Network is used to motivate the low frequency pixel and Morphological filter is applied to the edge detected image for finding the features in the images. This is an real time transformations which will give better results in SAR image processing, video processing, stereo based reconstruction of depth and width of the features present in the image.

     

Multi-resolution analysis techniques and nonlinear PCA for hybrid pansharpening applications

Hyperspectral images have a higher spectral resolution (i.e., a larger number of bands covering the electromagnetic spectrum), but a lower spatial resolution with respect to multispectral or panchromatic acquisitions. For increasing the capabilities of the data in terms of utilization and interpretation, hyperspectral images having both high spectral and spatial resolution are desired. This can be achieved by combining the hyperspectral image with a high spatial resolution panchromatic image. These techniques are generally known as pansharpening and can be divided into component substitution (CS) and multi-resolution analysis (MRA) based methods. In general, the CS methods result in fused images having high spatial quality but the fused images suffer from spectral distortions. On the other hand, images obtained using MRA techniques are not as sharp as CS methods but they are spectrally consistent. Both substitution and filtering approaches are considered adequate when applied to multispectral and PAN images, but have many drawbacks when the low-resolution image is a hyperspectral image. Thus, one of the main challenges in hyperspectral pansharpening is to improve the spatial resolution while preserving as much as possible of the original spectral information. An effective solution to these problems has been found in the use of hybrid approaches, combining the better spatial information of CS and the more accurate spectral information of MRA techniques. In general, in a hybrid approach a CS technique is used to project the original data into a low dimensionality space. Thus, the PAN image is fused with one or more features by means of MRA approach. Finally the inverse projection is used to obtain the enhanced image in the original data space. These methods, permit to effectively enhance the spatial resolution of the hyperspectral image without relevant spectral distortions and on the same time to reduce the computational load of the entire process. In particular, in this paper we focus our attention on the use of Nonlinear Principal Component Analysis (NLPCA) for the projection of the image into a low dimensionality feature space. However, if on one hand the NLPCA has been proved to better represent the intrinsic information of hyperspectral images in the feature space, on the other hand an analysis of the impact of different fusion techniques applied to the nonlinear principal components in order to define the optimal framework for the hybrid pansharpening has not been carried out yet. More in particular, in this paper we analyze the overall impact of several widely used MRA pansharpening algorithms applied in the nonlinear feature space. The results obtained on both synthetic and real data demonstrate that an accurate selection of the pansharpening method can lead to an effective improvement of the enhanced hyperspectral image in terms of spectral quality and spatial consistency, as well as a strong reduction in the computational time.     

Antialiasing filter design for subpixel downsampling via frequency-domain analysis

In this paper, we are concerned with image downsampling using subpixel techniques to achieve superior sharpness for small liquid crystal displays (LCDs). Such a problem exists when a high-resolution image or video is to be displayed on low-resolution display terminals. Limited by the low-resolution display, we have to shrink the image. Signal-processing theory tells us that optimal decimation requires low-pass filtering with a suitable cutoff frequency, followed by downsampling. In doing so, we need to remove many useful image details causing blurring. Subpixel-based downsampling, taking advantage of the fact that each pixel on a color LCD is actually composed of individual red, green, and blue subpixel stripes, can provide apparent higher resolution. In this paper, we use frequency-domain analysis to explain what happens in subpixel-based downsampling and why it is possible to achieve a higher apparent resolution. According to our frequency-domain analysis and observation, the cutoff frequency of the low-pass filter for subpixel-based decimation can be effectively extended beyond the Nyquist frequency using a novel antialiasing filter. Applying the proposed filters to two existing subpixel downsampling schemes called direct subpixel-based downsampling (DSD) and diagonal DSD (DDSD), we obtain two improved schemes, i.e., DSD based on frequency-domain analysis (DSD-FA) and DDSD based on frequency-domain analysis (DDSD-FA). Experimental results verify that the proposed DSD-FA and DDSD-FA can provide superior results, compared with existing subpixel or pixel-based downsampling methods.     

Sharp Cutoff Microwave Filters

A class of sharp cutoff filters using combinations of lumped constant and distributed constant reactance have been analyzed and a test made of one type. The filters are developed in accordance with image parameter theory and are m-derived. Both high-pass and low-pass types are analyzed. The improvements over previous sharp-cutoff image parameter filters are predictable band limits and more predictable response. The derivations hold for all frequencies and are not approximations good only for short lengths of distributed constant reactance. Also, this class of filters have much sharper cutoffs than can be obtained with an equivalent number of sections designed using modern network theory. Some of these filters have fairly flat response close to the sharp-cutoff and are useful as end-matching sections. Curves and design equations are presented for three types---two high-pass and one low-pass filter. A seven-section high-pass filter was designed and tested. Its cutoff rate was 87db in a 3 per cent bandwidth located in the 300-Mc region. The pass-band width was greater than 30 per cent.     

基于MO-OTA-C的n阶通用电流模式滤波器

以OTA-C为基本模块,在其输入端加入一个电流信号,使输出电流受其控制,然后利用多端输出(MO)的OTA-C实现n阶通用电流模式滤波器的设计。该滤波器能实现低通、高通、带通、带阻和全通功能,n阶滤波器仅需要n个OTA和n个电容,便于集成。以三阶Butterworth滤波器为例,进行低通、带通和高通仿真。理论分析与Spice仿真表明,所设计的滤波器结构正确可行。     

Low-pass and high-pass filters using coaxial-type dielectric resonators

This paper proposes new low-pass and high-pass filters using coaxial-type dielectric resonators. The low-pass filter has a LC-type circuit structure and is composed of three inductances and two resonance circuits. The resonance circuits are the open-ended coaxial-type dielectric resonators whose length is λg/4. The high-pass filter has a CL-type circuit structure. Two high-pass filters are described, one of them is composed of three capacitances andtwo resonance circuits, the other is composed of five capacitances and four resonance circuits. The operating frequency range of the low-pass filter is 0.13–0.9 GHz and the cutoffency is 900 MHz, and the insertion loss is 0.3 dB. The corresponding quantities of the high-pass filter are 0.9–2.5 GHz, 900 MHz, and 0.3 dB, respectively.     

Third order voltage mode universal filter using CCCII

This paper brings a multi input single output third order universal filter using second generation current controlled current conveyor (CCCII). The proposed structure consists of three CCCIIs and three capacitors for all filter responses. The universal filter offers all five sections of filter responses, namely: low-pass, high-pass, band-pass, notch filter and all-pass. The topology can provide all filter responses by the proper selection of input. The proposed universal filter offers some important features like no external resistor, minimum number of CCCIIs, no component matching constraint for filter response, electronically adjustable filter response using bias current of CCCIIs and many more. The workability of the proposed structure is well verified with PSPICE in which simulation results follow the theoretical one.     

Pan-sharpening via multi-scale and multiple deep neural networks

Interpreting remote sensing images by combining manual visual interpretation and computer automatic classification and recognition is an important application of human–computer interaction (HCI) in the field of remote sensing. Remote sensing images with high spatial resolution and high spectral resolution is an important basis for automatic classification and recognition. However, such images are often difficult to obtain directly. In order to solve the problem, a novel pan-sharpening method via multi-scale and multiple deep neural networks is presented. First, the non-subsampled contourlet transform (NSCT) is employed to decompose the high resolution (HR)/low resolution (LR) panchromatic (PAN) images into the high frequency (HF)/low frequency (LF) images, respectively. For pan-sharpening, the training sets are only sampled from the HF images. Then, the DNN is utilized to learn the feature of the HF images in different directions of HR/LR PAN images, which is trained by the image patch pair sampled from HF images of HR/LR PAN images. Moreover, in the fusion stage, NSCT is also employed to decompose the principal component of initially amplified LR multispectral (MS) image obtained by the transformation of adaptive PCA (A-PCA). The HF image patches of LR MS, as the input data of the trained DNN, go through forward propagation to obtain the output HR MS image. Finally, the output HF sub-band images and the original LF sub-band images of LR MS image fuse into a new sub-band set. The inverse transformations of NSCT and A-PCA , residual compensation are conducted to obtain the pan-sharpened HR MS. The experimental results show that our method is better than other well-known pan-sharpening methods.     

面向图像超分辨率的紧凑型多径卷积神经网络算法研究

为改善单帧图像分辨率退化问题,减少网络参数,本文提出一种基于紧凑型多径结构卷积神经网络的图像超分辨率重构算法。本文算法采用多径结构模型充分使用低分辨率图像信息,并利用残差学习策略学习低分辨率和高分辨率图像间残差信息以重建高分辨率图像。当卷积核数量有限时,含有ReLU的网络重构性能表现不佳,因此引入最大特征图激活函数,增强网络泛化能力,使网络结构更加紧凑,以捕捉具有竞争性特征,完成图像超分辨率重构。实验结果表明,本文方法具有良好的重构能力,图像清晰度和边缘锐度明显提高,在客观评价和主观视觉效果方面优于当前主流的超分辨率重构方法。为便携式高性能超分辨率重构奠定理论基础。      

Three-input single-output second-order filters using current-feedback amplifiers

In this study, a novel second order universal filter using current-feedback amplifier, commercially available active component, is presented. The signal-flow graph method is used to synthesize the filter. The proposed filter has three high impedance input and one output, (multiple input single output (MISO) configuration). It can generate all biquadratic filtering functions namely: low-pass (LP), band-pass (BP), high-pass (HP), band-reject (BR) and all-pass (AP) at the output terminal by selecting different input signal combinations. The validity of the proposed circuits is demonstrated by simulations.     

Estimation of the Number of Decomposition Levels for a Wavelet-Based Multiresolution Multisensor Image Fusion

The wavelet-based scheme for the fusion of multispectral (MS) and panchromatic (PAN) imagery has become quite popular due to its ability to preserve the spectral fidelity of the MS imagery while improving its spatial quality. This is important if the resultant imagery is used for automatic classification. Wavelet-based fusion results depend on the number of decomposition levels applied in the wavelet transform. Too few decomposition levels result in poor spatial quality fused images. On the other hand, too many levels reduce the spectral similarity between the original MS and the pan-sharpened images. If the shift-invariant wavelet transform is applied, each excessive decomposition level results in a large computational penalty. Thus, the choice of the number of decomposition levels is significant. In this paper, PAN and MS image pairs with different resolution ratios were fused using the shift-invariant wavelet transform, and the optimal decomposition levels were determined for each resolution ratio. In general, it can be said that the fusion of images with larger resolution ratios requires a higher number of decomposition levels. This paper provides the practitioner an understanding of the tradeoffs associated with the computational demand and the spatial and spectral quality of the wavelet-based fusion algorithm as a function of the number of decomposition levels     

Current-mode electronically tunable biquadratic filters consisting of only CCCIIs and grounded capacitors

In this paper, a current-mode (CM) analog filter for simultaneously realizing high output impedance low-pass, band-pass and high-pass analog responses besides high output impedance notch and all-pass analog filter responses with interconnection of the relevant output currents, is presented. Also, two CM filters for simultaneously providing high output impedance universal filter responses are derived from the proposed one. All of the introduced CM topologies employ a canonical number of only grounded capacitors without requiring any resistors, and do not need critical component matching conditions. All of the developed circuits have low input impedance and high output impedance resulting in easy cascadability with other CM ones. Frequency dependent non-ideal gain and parasitic impedance effects on the performance of the presented first filter are investigated as examples. In order the show the performance of the filter and verify the theory, simulations are accomplished with SPICE program.     

基于二维DFT域全相位滤波的图像多分辨率分析

图像多分辨率分析在信号滤波、图像除噪、图像 融合、图像边缘检测领域中应用广泛。该文设计了一种新的 图像多分辨率分析方法,通过对全相位系统函数进行谱分解,实现了基于全相位的严格功率 互补的高低通滤波器设计, 按照全相位处理的基本理论,选择不同的正交变换方式和基窗函数可以方便地设计出具有不 同分析/合成效果的全相位波 包。实验表明,DFT域全相位分析滤波器可以实现对图像的多层分解,由合成滤波器还原得 到的图像误差几乎为零。在 图像数据压缩、自适应除噪方面具有较为广泛的应用前景。     

激光雷达三维距离像超分辨重构方法研究

针对目前激光雷达三维距离像分辨率低的问题,使用成本低且有效的图像处理方法获得高分辨三维距离像。首先,利用多传感器系统的特点,将低分辨率Gm-APD激光雷达与高分辨率ICCD激光雷达相结合,获得配准后的低分辨距离像和高分辨强度像,然后,提出了一种改进的图像引导算法实现低分辨图像超分辨重构。该方法使用马尔科夫随机场模型,定义了全局能量函数,该函数将距离保真项和正则化项相结合,通过求解优化模型获得高分辨三维距离像。通过对仿真图像和激光雷达距离像的超分辨重构处理,以主观视觉效果和图像质量客观评价指标来验证此方法。实验结果表明,该方法提高了距离像的分辨率,且很好地保护了图像的边缘结构,在无参考图像质量评价指标上较双三次插值、引导滤波和TGV取得更优值。     

基于OTRA电流模式二阶通用滤波器的设计

鉴于单个OTRA电流模式滤波器未见报道,以CCⅡ二阶通用电流模式滤波器为原型,利用1个OTRA,1个MOS电压跟随器,1个CMOS电压反相器,3个电阻和2个电容,构成了二阶通用电流模式滤波器,可同时获得高通、带通和低通输出。与传统电路相比,该电路能减小寄生电容的影响,因而有较高的稳定性;调节极点角频率与品质因素的元素多,因而调整方便,且通带增益可调范围广,无源灵敏度较低,电路结构简单,便于电控调谐,特别适合单片集成技术。     

Landsat ETM+ and SAR image fusion based on generalized intensity Modulation

This work presents a novel multisensor image fusion algorithm, which extends panchrmomatic sharpening of multispectral (MS) data through intensity modulation to the integration of MS and synthetic aperture radar (SAR) imagery. The method relies on SAR texture, extracted by ratioing the despeckled SAR image to its low-pass approximation. SAR texture is used to modulate the generalized intensity (GI) of the MS image, which is given by a linear transform extending intensity-hue-saturation transform to an arbitrary number of bands. Before modulation, the GI is enhanced by injection of high-pass details extracted from the available panchrmomatic image by means of the "a/spl grave/-trous" wavelet decomposition. The texture-modulated panchrmomatic-sharpened GI replaces the GI calculated from the resampled original MS data. Then, the inverse transform is applied to obtain the fusion product. Experimental results are presented on Landsat-7 Enhanced Thematic Mapper Plus and European Remote Sensing 2 satellite images of an urban area. The results demonstrate accurate spectral preservation on vegetated regions, bare soil, and also on textured areas (buildings and road network) where SAR texture information enhances the fusion product, which can be usefully applied for both visual analysis and classification purposes.     

Design of linear phase M-channel perfect reconstruction FIR filterbanks

We propose two approaches to design M channel nonparaunitary filter banks that satisfy perfect reconstruction (PR) and linear phase (LP) properties. In the first approach, the PR condition is imposed on only a high-pass filter. Although this method does not require nonlinear optimization, it has a demerit in that the order of a high-pass filter becomes high. In the second approach, two filters are optimized simultaneously using a Lagrange-Newton method. We can design PR filter banks that have the same length. The PR constraint is also formulated as a linear and nonlinear equation of the analysis filter coefficients. Finally, some design examples are included     

L1范数的图像超分辨率重建改进算法

介绍了超分辨率图像重建的数学模型和基于L1范数的超分辨率重建算法。针对在所观察到的低分辨率图像不足情况下的超分辨率重建,在L1范数重建算法框架下,提出了一种新的代价方程,在其中增加了关于丢失的低分辨率观察信息的保真度项和正则化项。该方法同时对高分辨率图像和丢失的观察信息进行迭代估计,并利用交替最小方法求解。实验结果表明,在获取低分辨率图像较少的情况下,提出的算法能够有效地改进重建的结果。     

带限测试系统对电磁脉冲波形参数的影响分析

从设计和研制实际测试系统的角度出发,对电磁脉冲的不失真测试带宽进行了分析和讨论。在分析电磁脉冲时频域特征的基础上,利用典型的二阶低通和高通滤波器传递函数模型,分别研究了测试系统中上、下限截止频率以及系统阻尼比对电磁脉冲波形参数的影响,并给出了一种在时域利用电磁脉冲波形参数误差来近似评估带限测试系统不失真测试带宽的方法,通过获得测试系统的-3dB带宽和阻尼比等参数设置,可用于指导实际测试系统的设计和研制。