An improved deconvolution method for X-ray coded imaging in inertial confinement fusion

In inertial confinement fusion （ICF）, X-ray coded imaging is considered as the most potential means to diagnose the compressed core. The traditional Richardson-Lucy （RL） method has a strong ability to deblur the image where the noise follows the Poisson distribution. However, it always suffers from over-fitting and noise amplification, especially when the signal-to-noise ratio of image is relatively low. In this paper, we propose an improved deconvolution method for X-ray coded imaging. We model the image data as a set of independent Gaussian distributions and derive the iterative solution with a maximum-likelihood scheme. The experimental results on X-ray coded imaging data demonstrate that this method is superior to the RL method in terms of anti-overfitting and noise suppression.

Encoding methods matching the 16×16 pixel CZT detector of a coded aperture gamma camera

With the advancements in nuclear energy,methods that can accurately obtain the spatial information of radioactive sources have become essential for nuclear energy safety.Coded aperture imaging technology is widely used because it provides two-dimensional distribution information of radioactive sources.The coded array is a major component of a coded aperture gamma camera,and it affects the key performance parameters of the camera.Currently,commonly used coded arrays such as uniformly redundant arrays(URAs)and modified uniformly redundant arrays(MURAs)have prime numbers of rows or columns and may lead to wastage of detector pixels.A 16×16 coded array was designed on the basis of an existing 16×16 multi-pixel position-sensitive cadmium zinc telluride detector.The digital signal-to-noise(SNR)ratio of the point spread function at the center of the array is 25.67.Furthermore,Monte Carlo camera models and experimental devices based on rank-13 MURA and rank-16 URA have been constructed.With the same angular resolution,the field size of view under rank-16 URA is 1.53 times that of under rank-13 MURA.Simulations(Am-241,Co-57,Ir-192,Cs-137)and experiments(Co-57)are conducted to compare the imaging performance between rank-16 URA and rank-13 MURA.The contrast-to-noise ratio of the reconstructed image of the rank-16 array is great and only slightly lower than that of rank-13 MURA.However,as the photon energy increases,the gap becomes almost negligible.

AUTOMATED IMAGE MATCHING WITH CODED POINTS IN STEREOVISION MEASUREMENT

A coding-based method to solve the image matching problems in stereovision measurement is presented. The solution is to add and append an identity ID to the retro-reflect point, so it can be identified efficiently under the complicated circumstances and has the characteristics of rotation, zooming, and deformation independence. Its design architecture and implementation process in details based on the theory of stereovision measurement are described. The method is effective on reducing processing data time, improving accuracy of image matching and automation of measuring system through experiments.

Elimination of the Background Noise of the Decoded Image in Fresnel Zone Plate Scanning Holography

A method of digitally high pass filtering in frequency domain is proposed to eliminate the background noise of the decoded image in Fresnel zone plate scanning holography. The high pass filter is designed as a circular stop, which should be suitable to suppressing the background noise significantly and remain much low frequency information of the object. The principle of high pass filtering is that the Fourier transform of the decoded image is multiplied with the high pass filter. Thus the frequency spectrum of the decoded image without the background noise is achieved. By inverse Fourier transform of the spectrum of the decoded image after multiplying operation, the decoded image without the background noise is obtained. Both of the computer simulations and the experimental results show that the contrast and the signal-to-noise ratio of the decoded image are significantly improved with digital filtering.

Efficient Quadtree based Fractal Image Coding Scheme in Wavelet Transform Domain *

This paper presents an efficient quadtree based fractal image coding scheme in wavelet transform domain based on the wavelet based theory of fractal image compression introduced by Davis. In the scheme, zerotrees of wavelet coefficients are used to reduce the number of domain blocks, which leads to lower bit cost required to represent the location information of fractal coding, and overall entropy constrained optimization is performed for the decision trees as well as for the sets of scalar quantizers and self quantizers of wavelet subtrees. Experiment results show that at the low bit rates, the proposed scheme gives about 1 dB improvement in PSNR over the reported results.

VLSI Implementation of a Wavelet Image Coder

A modular architecture for two dimension (2 D) discrete wavelet transform (DWT) is designed.The image data can be wavelet transformed in real time,and the structure can be easily scaled up to higher levels of DWT.A fast zerotree image coding (FZIC) algorithm is proposed by using a simple sequential scan order and two flag maps.The VLSI structure for FZIC is then presented.By combining 2 D DWT and FZIC,a wavelet image coder is finally designed.The coder is programmed,simulated,synthesized,and successfully verified by ALTERA CPLD.

Technique of Error Concealment for Block-Based Image Coding Using Genetic Algorithm

Since real world communication channels are not error free, the coded data transmitted on them may be corrupted, and block based image coding systems are vulnerable to transmission impairment. So the best neighborhood match method using genetic algorithm is used to conceal the error blocks. Experimental results show that the searching space can be greatly reduced by using genetic algorithm compared with exhaustive searching method, and good image quality is achieved. The peak signal noise ratios(PSNRs) of the restored images are increased greatly.

An Adaptive Block-Based Fractal Image Coding Scheme

Based on Jacquin's work. this paper presents an adaptive block-based fractal image coding scheme. Firstly. masking functions are used to classify range blocks and weight the mean Square error (MSE) of images. Secondly, an adaptive block partition scheme is introduced by developing the quadtree partition method. Thirdly. a piecewise uniform quantization strategy is appled to quantize the luminance shifting. Finally. experiment results are shown and compared with what reported by Jacquin and Lu to verify the validity of the methods addressed by the authors.

Chaos-based encryption for fractal image coding

A chaos-based cryptosystem for fractal image coding is proposed. The Renyi chaotic map is employed to determine the order of processing the range blocks and to generate the keystream for masking the encoded sequence. Compared with the standard approach of fraetal image coding followed by the Advanced Encryption Standard, our scheme offers a higher sensitivity to both plaintext and ciphertext at a comparable operating efficiency. The keystream generated by the Renyi chaotic map passes the randomness tests set by the United States National Institute of Standards and Technology, and so the proposed scheme is sensitive to the key.

Source extension based on ε-entropy

It is known by entropy theory that image is a source correlated with a certain characteristic of probability. The entropy rate of the source and ε- entropy (rate-distortion function theory) are the information content to identify the characteristics of video images, and hence are essentially related with video image compression. They are fundamental theories of great significance to image compression, though impossible to be directly turned into a compression method. Based on the entropy theory and the image compression theory, by the application of the rate-distortion feature mathematical model and Lagrange multipliers to some theoretical problems in the H.264 standard, this paper presents a new the algorithm model of coding rate-distortion. This model is introduced into complete test on the capability of the test model of JM61e (JUT Test Model). The result shows that the speed of coding increases without significant reduction of the rate-distortion performance of the coder.

Mean shift based log-Gabor wavelet image coding

In this paper, we propose a sparse overcomplete image approximation method based on the ideas of overcomplete log-Gabor wavelet, mean shift and energy concentration. The proposed approximation method selects the necessary wavelet coefficients with a mean shift based algorithm, and concentrates energy on the selected coefficients. It can sparsely approximate the original image, and converges faster than the existing local competition based method. Then, we propose a new compression scheme based on the above approximation method. The scheme has compression performance similar to JPEG 2000. The images decoded with the proposed compression scheme appear more pleasant to the human eyes than those with JPEG 2000.

Compact MPPC-based coded aperture imaging camera for dual-particle detection

Purpose Fast neutrons and gamma-ray imaging detection is an effective way to detect and identify radioactive material in the field of nuclear security.A compact coded aperture imaging(CAI)camera was designed to be sensitive to both gamma and neutron radiation based on plastic scintillators and multi-pixel photon counters(MPPC).Methods MPPCs coupling with the 13×13 pixelated plastic scintillators one-to-one were utilized to reduce the scale of the CAI system while maintaining good positional performance.The symmetric charge division(SCD)circuit was adopted to reduce the 169 signals output from the MPPC array to 26.Each waveform was collected and processed with four Domino Ring Sampler 4(DRS4)chips and two 16-channel analog-to-digital converter(ADC)modules.As the pulse shapes of fast neutrons would be broadened after elastic scattering multiple times in the scintillators,the Anger-Logic method was applied to eliminate multiple elastic scattering events so that good pulse shape discrimination(PSD)performance can be achieved.Results The imaging and detection ability of the camerawas evaluated using the 241Am-Be(5.9×10^(5) n/s)neutron source and 137Cs(370 MBq)gammasource.The camera can be used to detect fast neutrons(0.5–10 MeV)and gammarays(0.2–2.5MeV).Furthermore,it can implement efficient neutron/gamma PSD capabilities in the mixed-field environment.The figure of merit(FOM)of the camera calculated at 400keVee energy cut is 0.93.Conclusion A compact MPPC-based CAI camera was designed to detect and discriminate fast neutrons and gamma rays.Its good PSD performance was well suited to distinguish fast neutrons from gamma rays in a dual-particle environment.The portable design makes it promising for complex monitoring scenarios in nuclear security.

FAST IMAGE ENCODING ALGORITHM BASED ON MEAN-MATCH CORRELATION VECTOR QUANTIZATION

A mean-match correlation vector quantizer (MMCVQ) was presented for fast image encoding. In this algorithm, a sorted codebook is generated regarding the mean values of all codewords. During the encoding stage, high correlation of the adjacent image blocks is utilized, and a searching range is obtained in the sorted codebook according to the mean value of the current processing vector. In order to gain good performance, proper THd and NS are predefined on the basis of experimental experiences and additional distortion limitation. The expermental results show that the MMCVQ algorithm is much faster than the full-search VQ algorithm, and the encoding quality degradation of the proposed algorithm is only 0.3～0.4 dB compared to the full-search VQ.

Design and Implementation of Verification Code Identification Based on Anisotropic Heat Kernel

Many websites use verification codes to prevent users from using the machine automatically to register,login,malicious vote or irrigate but it brought great burden to the enterprises involved in internet marketing as entering the verification code manually.Improving the verification code security system needs the identification method as the corresponding testing system.We propose an anisotropic heat kernel equation group which can generate a heat source scale space during the kernel evolution based on infinite heat source axiom,design a multi-step anisotropic verification code identification algorithm which includes core procedure of building anisotropic heat kernel,settingwave energy information parameters,combing outverification codccharacters and corresponding peripheral procedure of gray scaling,binarizing,denoising,normalizing,segmenting and identifying,give out the detail criterion and parameter set.Actual test show the anisotropic heat kernel identification algorithm can be used on many kinds of verification code including text characters,mathematical,Chinese,voice,3D,programming,video,advertising,it has a higher rate of 25%and 50%than neural network and context matching algorithm separately for Yahoo site,49%and 60%for Captcha site,20%and 52%for Baidu site,60%and 65%for 3DTakers site,40%,and 51%.for MDP site.

Formal Photograph Compression Algorithm Based on Object Segmentation

Small storage space for photographs in formal documents is increasingly necessary in today＇s needs for huge amounts of data communication and storage. Traditional compression algorithms do not sufficiently utilize the distinctness of formal photographs. That is, the object is an image of the human head, and the background is in unicolor. Therefore, the compression is of low efficiency and the image after compression is still space-consuming. This paper presents an image compression algorithm based on object segmentation for practical high-efficiency applications. To achieve high coding efficiency, shape-adaptive discrete wavelet transforms are used to transformation arbitrarily shaped objects. The areas of the human head and its background are compressed separately to reduce the coding redundancy of the background. Two methods, lossless image contour coding based on differential chain, and modified set partitioning in hierarchical trees （SPIHT） algorithm of arbitrary shape, are discussed in detail. The results of experiments show that when bit per pixel （bpp）is equal to 0.078, peak signal-to-noise ratio （PSNR） of reconstructed photograph will exceed the standard of SPIHT by nearly 4dB.

A HIGH SPEED ADAPTIVE FRACTAL IMAGE CODING ALGORITHM USING FLEXIBLE CLASSIFICATION TECHNIQUE

Traditionally, fractal image compression suffers from lengthy encoding time in measure ofhours. In this paper, combined with characteristlcs of human visual system, a flexible classification technique is proposed. This yields a corresponding adaptive algorithm which can cut down the encoding timeinto second's magnitude. Experiment results suggest that the algorithm can balance the overall encodingperformance efficiently, that is, with a higher speed and a better PSNR gain.

Lifting Scheme Based SPIHT Still Image Coding

In order to eliminate float-point operations for fast wavelet transform, an integer D9/7 biorthogonal reversible wavelet transform was accomplished by lifting scheme. The lifting scheme based wavelet transform can be finished by addition and shift simply. It improved the quality of reconstructive image and greatly reduced the computational complexity due to integer operation. It is suitable for real-time image coding on hardware such as DSP. The simulation results show that the lifting scheme based SPIHT is prior to traditional wavelet based SPHIT in quality and complexity.

Improvement of Camera Calibration Accuracy Based on Periodic Arrangement Characteristics of Calibration Target Pattern

Conventional camera calibration that employs calibration targets is a commonly used method to acquire a camera’s intrinsic and/or extrinsic parameters. The calibration targets are usually designed as periodic arrays of simple high-contrast patterns that provide highly accurate world coordinate system points and the corresponding image pixel coordinate system points. The existing pixel coordinate extraction algorithms can reach a sub-pixel level; however, they treat each single pattern in one image as an independent individual, which makes it difficult to further improve extraction accuracy. In this paper, a novel method is proposed by utilizing the periodic arrangement characteristics of the calibration target pattern as a global constraint to improve the calibration accuracy. Based on a camera’s pinhole model, the intersection point of two fitted curves is used as an optimized pixel point to replace the initial one. Following the pixel coordinate optimization procedures, experiments were performed using real data from a 3D laser line scanner and a dynamic precision calibration target. Our results show that the relative errors of camera homography matrix elements obtained by the proposed optimization method were reduced compared with the commonly used method. The average coordinate measurement accuracy can be improved by nearly 0.05 mm. It is shown that the proposed optimization method can enhance the camera calibration accuracy, especially when the extracted pixels are of poorer precision. © 2017 Tianjin University and Springer-Verlag Berlin Heidelberg

High performance scalable image coding

A high performance scalable image coding algorithm is proposed. The salient features of this algorithm are the ways to form and locate the significant clusters. Thanks to the list structure, the new coding algorithm achieves fine fractional bit-plane coding with negligible additional complexity. Experiments show that it performs comparably or better than the state-of-the-art coders. Furthermore, the flexible codec supports both quality and resolution scalability, which is very attractive in many network applications.

An Adaptive Method of Image CompressionBased on Wavelet Analysis

Through research for image compression based on wavelet analysis in recent years, we put forward an adaptive wavelet decomposition strategy. Whether sub-images are to be decomposed or not are decided by their energy defined by certain criterion. Then we derive the adaptive wavelet decomposition tree (AWDT) and the way of adjustable compression ratio. According to the feature of AWDT, this paper also deals with the strategies which are used to handle different sub-images in the procedure of quantification and coding of the wavelet coefficients. Through experiments, not only the algorithm in the paper can adapt to various images, but also the quality of recovered image is improved though compression ratio is higher and adjustable. When their compression ratios are near, the quality of subjective vision and PSNR of the algorithm are better than those of JPEG algorithm.