Adaptive Median Filtering Algorithm Based on Divide and Conquer and Its Application in CAPTCHA Recognition

As the first barrier to protect cyberspace,the CAPTCHA has made significant contributions to maintaining Internet security and preventing malicious attacks.By researching the CAPTCHA,we can find its vulnerability and improve the security of CAPTCHA.Recently,many studies have shown that improving the image preprocessing effect of the CAPTCHA,which can achieve a better recognition rate by the state-of-theart machine learning algorithms.There are many kinds of noise and distortion in the CAPTCHA images of this experiment.We propose an adaptive median filtering algorithm based on divide and conquer in this paper.Firstly,the filtering window data quickly sorted by the data correlation,which can greatly improve the filtering efficiency.Secondly,the size of the filtering window is adaptively adjusted according to the noise density.As demonstrated in the experimental results,the proposed scheme can achieve superior performance compared with the conventional median filter.The algorithm can not only effectively detect the noise and remove it,but also has a good effect in preservation details.Therefore,this algorithm can be one of the most strong tools for various CAPTCHA image recognition and related applications.

Median Filtering Forensics Scheme for Color Images Based on Quaternion Magnitude-Phase CNN

In the paper,a convolutional neural network based on quaternion transformation is proposed to detect median filtering for color images.Compared with conventional convolutional neural network,color images can be processed in a holistic manner in the proposed scheme,which makes full use of the correlation between RGB channels.And due to the use of convolutional neural network,it can effectively avoid the one-sidedness of artificial features.Experimental results have shown the scheme’s improvement over the state-of-the-art scheme on the accuracy of color image median filtering detection.

Median Filtering Detection Based on Quaternion Convolutional Neural Network

Median filtering is a nonlinear signal processing technique and has an advantage in the field of image anti-forensics.Therefore,more attention has been paid to the forensics research of median filtering.In this paper,a median filtering forensics method based on quaternion convolutional neural network(QCNN)is proposed.The median filtering residuals(MFR)are used to preprocess the images.Then the output of MFR is expanded to four channels and used as the input of QCNN.In QCNN,quaternion convolution is designed that can better mix the information of different channels than traditional methods.The quaternion pooling layer is designed to evaluate the result of quaternion convolution.QCNN is proposed to features well combine the three-channel information of color image and fully extract forensics features.Experiments show that the proposed method has higher accuracy and shorter training time than the traditional convolutional neural network with the same convolution depth.

An Adaptive Median Filter Algorithm Based on B-spline Function

According to the B-spline convolution mask, first, the contrast sensitiveness (CS) is computed and then is viewed as a noise sensitiveness coeficient (NSC) to adaptively determine a noise-recognized threshold value. Based on the noise density function (NDF) in a 3×3 window, the filtering window size is adaptively adjusted, and then a median filter is used to eliminate the noise-marked pixels. The experiment results show that the proposed algorithm can preserve image detail information well and effectively remove the noises, particularly the impulse noises that is also called salt-and-pepper noises superimposed on the computed tomography (CT) and magnetic resonance imaging (MRI) medical images.

Digital Filter Algorithm Based on Morphological Lifting Scheme and Median Filter

When the circuits in which electronic products are fitted are disturbed by various interrupting signals, wave distortions occur to the normal voltage signals of these circuits.These wave distortions influence the normal operation and life cycle of electronic products. To eliminate the harmful effects of interrupting signals on electronic products, in this paper, a digital filter algorithm based on morphological lifting scheme and median filter(MLS-MF), which will be used to filter various interrupting signals existing in the circuits in which electronic products are fitted, is proposed. A variety of interrupting signals have been included in simulation studies, and simulation results have demonstrated the effectiveness and feasibility of the proposed digital filter algorithm in high frequency continuous interference, random background noise and damped oscillatory transient interference filter.

Adaptive Threshold Median Filter for Multiple-Impulse Noise

Attenuating the noises plays an essential role in the image processing. Almost all the traditional median filters concern the removal of impulse noise having a single layer,whose noise gray level value is constant. In this paper,a new adaptive median filter is proposed to handle those images corrupted not only by single layer noise. The adaptive threshold median filter(ATMF) has been developed by combining the adaptive median filter(AMF) and two dynamic thresholds. Because of the dynamic threshold being used,the ATMF is able to balance the removal of the multiple-impulse noise and the quality of image. Comparison of the proposed method with traditional median filters is provided. Some visual examples are given to demonstrate the performance of the proposed filter.

LAPPED TRANSFORM DOMAIN INTERFERENCE EXCISION USING MODIFIED MEDIAN FILTER

A novel communication receiver which uses lapped transform(LT) incorporating modified median filter(MMF) algorithm was designed for narrow band interference(NBI) excision.Comparing to traditional Fourier Transform,LT has longer basis vectors,less spectral leakage,thus better frequency resolution.The LT domain MMF algorithm takes full advantages of the direct sequence spread spectrum signal,as well as the characteristics of LT,performs the transform domain filtering twice.The first filtering locates the position of interference and mitigates most of them.The second filtering is performed in a small neighborhood of the located interference.So LT domain MMF algorithm can completely mitigate the interference without distorting the desired signal.The simulation results demonstrate the improved BER(Bit Error Rate)performance and increased robustness of our receiver.

Refinement of Enhanced Speech Using Hybrid-Median Filter and Harmonic Regeneration Approach

This study proposes a post-processor to improve the harmonic structure of a vowel in an enhanced speech, enabling the speech quality to be improved. Initially, a speech enhancement algorithm is employed to reduce the background noise for a noisy speech. Hence the enhanced speech is post-processed by a hybrid-median filter to reduce the musical effect of residual noise. Since the harmonic spectra are impacted by background noise and a speech enhancement process, the quality of a vowel is deteriorated. A harmonic regenerated method is developed to improve the quality of post-processed speech. Experimental results show that the proposed method can improve the quality of post-processed speech by adequately regenerating harmonic spectra.

Iterative Adaptive Median Filter for Impulse Noise Cancellation

基于推动噪音的特征，作者建立一个新过滤器，到图象的 charactics 的反复的适应中部的过滤器( IAMF ) .According 由推动噪音弄脏，他们证实重量 ftnction 与反复的算法结合了消除 noises.In IAMF 过滤器过程，因为噪音点不参予计算，他们不在图象影响正常的点，因此， IAMF 能保留详细很好，在处理图象，和 simult

Generalized Correlativity of Median Filtering Operator on Signals

The generalized correlativity of input signal and output signal of a stack filtering operator is defined and used for numerously measuring these filtering operators's behavior in removing noise in signals. We show that under the criterion of the generalized correlativity, of stack filtering operators the median filtering operator is optimal, which implies that this filtering operator possesses better filtering behavior than the others.

Some Problems of 2D Morphological and Median Filters

In this paper we mainly discussed some problems of 2D morpnological and median filters .The differences between 1D and 2D morphological and median filters arc also described. It can be seen that many propcrties of ID finers arc invalid for 2D filters. Som cxamples and cxpcriments are gived to show these problems.

Graphic Processor Unit Acceleration of Multi-exposure Image Fusion with Median Filter

A fast Graphic Processor Unit(GPU)accelerate algorithm of multiexposure image fusion with median filter is presented in this paper.The proposed algorithm fuses images in YUV space instead of RGB space compared to traditional image fusion method.Furthermore,in YUV space the brightness components and the chromatism components were weighted fused separately with median filter.At last the filtered images were transferred to RGB and merged to the final fusion image.In the GPU acceleration part,three parallel methods were proposed,including sequence images concurrent execution,adjacent kernels merge,and parallel median filter techniques,to expand the concurrency of the algorithm on the GPU platform.In the experimental results,a 16–21 times speedup was obtained compared to the CPU implementation and up to 60 fps performance was achieved in a 1000*1000*6 multi-exposure sequence image fusion case.The results in the experiment demonstrate the high efficiency and high availability of our proposed method.

Wavelet domain denoising method based on multistage median filtering

There are two main problems in the threshold denoising method based on wavelet transform. One is the difficulty of threshold selection, and the other is the inconsistence of the dip and curved events in the low signal-to-noise ratio (SNR) seismic data after denoising. In image denoising, multistage median filtering can preserve the details of the signal. So we proposed a denoising algorithm in wavelet transform domain based on multistage median filtering. Using this method the flat region and the edge region are differentiated by the difference between the maximum mid-value and the minimum mid-value, which preserves the details, thus improves the denoising effect. The simulation data and the real data processing results reveal that this method has stronger ability in separating signal from noise than that of the threshold denoising method.

Convergence of the median filterings of sequences

Suppose that x={x（n）}n∈Z is a sequence of real numbers. For each p∈N, x（p）={x（p）（n）}n∈Z is the resulting sequence of x through p times median filterings with window 2k+1. It is proved that when p→∞, both x（2p） and x（2p-1） are convergent. Thus the problem of convergence of the median filters of infinite-length sequences is completely solved.

Recurrent sequences in median filters (II)

1 Introduction Throughout this note k denotes a fixed integer and k】1. Let x={x(n)}_n=0, ±, ±2,… be a real sequence. For each integer n, we denote by x(n) the median value of the following 2k+1 numbers: x(n-k), x(n-k+1), …, x(n),…, x(n+k-1), x(n+k). By this permuting operation, the sequence x={x(n)} is transformed

INFINITE-LENGTH ROOTS OF MEDIAN FILTERS

This paper is a systematic study of the properties of infinite-length roots of median filters. We have succeeded in characterizing all the roots of median filters, especially roots of the second category. Special emphasis is placed on the structure of infinite-length roots of the second category.

Recurrent sequences in median filters (Ⅰ)

1 Introduction In this note k denotes a fixed integer and k≥2. Let x={x（n）}n=0,±1,±2,… be a real sequence. For each integer n, we denote by x1（n） the median value of the following 2k+1 numbers: x（n-k）, x（n-k+1）,…, x（n）,…,

Recognition of Partially Occluded Objects Based on Segmentation by Median Filtering of Extended Direction Code

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面向电力设备红外图像的混合噪声去除方法研究

电力设备的红外图像在采集传输过程中,易受高斯噪声与脉冲噪声的影响从而破坏图像的真实信息,为满足图像处理过程对图像质量的要求,文中提出了一种针对红外图像混合噪声的滤除方法。首先利用三方加权稀疏编码(TWSC)模型有效滤除红外图像中的高斯噪声,然后利用图像结构纹理分解结合中值滤波算法实现剩余脉冲噪声的分离与去除,实现在滤除红外图像混合噪声的同时较好地保持图像的边缘结构信息,结合实例分析表明文中方法能够有效滤除噪声并获得较高的峰值信噪比(PSNR)与结构相似度(SSIM)。