Image Tamper Detection and Multi-Scale Self-Recovery Using Reference Embedding with Multi-Rate Data Protection

This paper proposes a multi-scale self-recovery(MSSR)approach to protect images against content forgery.The main idea is to provide more resistance against image tampering while enabling the recovery process in a multi-scale quality manner.In the proposed approach,the reference data composed of several parts and each part is protected by a channel coding rate according to its importance.The first part,which is used to reconstruct a rough approximation of the original image,is highly protected in order to resist against higher tampering rates.Other parts are protected with lower rates according to their importance leading to lower tolerable tampering rate(TTR),but the higher quality of the recovered images.The proposed MSSR approach is an efficient solution for the main disadvantage of the current methods,which either recover a tampered image in low tampering rates or fails when tampering rate is above the TTR value.The simulation results on 10000 test images represent the efficiency of the multi-scale self-recovery feature of the proposed approach in comparison with the existing methods.

Study of Spherulite Growth Rate and Morphology of Polypropylenebased Blends by Image Processing Technology

The method for measuring the spherulite growth rate and studying the morphology of polypropylene - based blends by image processing technology is described. The main advantages of this method, as compared to existing techniques, are: better reliability; reproducibility; ease of manipulation. Such an approach provides a means of measuring the rate of spherulite growth. In this study, isotactic polypropylene (PP), polystyrene (PS)/PP, and polybutylene terephthalate (PBT)/PP have been studied. The results show that the technology of image analysis is very useful in the study of the kinetics of crystallization of polymer.

An Improved SPIHT Algorithm for Image Compression in Low Bit Rate

Aiming at shortage of the SPIHT algorithm, an improved image compression algorithm is proposed, in order to overcome the shortcomings of decoding image quality and coding time, LS9/7 lifting wavelet transform is adopted. According to the characteristics of the human visual system (HVS), the scanning mode and the method to determine the threshold of algorithm are changed to improve the quality of reconstruction image. On the question of repeating scan of SPIHT algorithm, using maximum list thought, greatly reduce the computation and save operating time. The experimental results have proved that the improved algorithm of image decoding time and the quality of reconstruction images are better than the original algorithm , especially in the case of low bit rate.

A rate control approach to distributed source coding for interferential multispectral image compression

Distributed source coding （DSC） is applied to interferential multispectral image compression owing to strong correlation among the image frames. Many DSC systems in the literature use feedback channel （FC） to control rate at the decoder, which limits the application of DSC. Upon an analysis of the image data, a rate control approach is proposed to avoid FC. Low-complexity motion compensation is applied first to estimate side information at the encoder. Using a polynomial fitting method, a new mathematical model is then derived to estimate rate based on the correlation between the source and side information. The experimental results show that our estimated rate is a good approximation to the actual rate required by FC while incurring a little bit-rate overhead. Our compression scheme performs comparable with the FC based DSC system and outperforms JPEG2000 significantly.

Processing of Landsat 8 Imagery and Ground Gamma-Ray Spectrometry for Geologic Mapping and Dose-Rate Assessment, Wadi Diit along the Red Sea Coast, Egypt

Maximum Likelihood (MLH) supervised classification of atmospherically corrected Landsat 8 imagery was applied successfully for delineating main geologic units with a good accuracy (about 90%) according to reliable ground truth areas, which reflected the ability of remote sensing data in mapping poorly-accessed and remote regions such as playa (Sabkha) environs, subdued topography and sand dunes. Ground gamma-ray spectrometric survey was to delineate radioactive anomalies within Quaternary sediments at Wadi Diit. The mean absorbed dose rate (D), annual effective dose equivalent (AEDE) and external hazard index (Hex) were found to be within the average worldwide ranges. Therefore, Wadi Diit environment is said to be radiological hazard safe except at the black-sand lens whose absorbed dose rate of 100.77 nGy/h exceeds the world average. So, the inhabitants will receive a relatively high radioactive dose generated mainly by monazite and zircon minerals from black-sand lens.

Particle Image Velocimetry Study of Turbulence Characteristics in a Vessel Agitated by a Dual Rushton Impeller

Particle Image Velocimetry （PIV） has been used to investigate turbulence characteristics in a 0.48 m diameter stirred vessel filled to a liquid height （ H = 1.4T ） of 0.67 m. The agitator had dual Rushton impellers of 0.19 m diameter （ D = 0.4T ）. The developed flow patterns depend on the clearance of the lower impeller above the base of the vessel, the spacing between the two impellers, and the submergence of the upper impeller below the liq- uid surface. Their combinations can generate three basic flow patterns, named, parallel, merging and diverging flows. The results of velocity measurement show that the flow characteristics in the impeller jet flow region changes very little for different positions. Average velocity, trailing vortices and shear strain rate distributions for three flow patterns were measured by using PIV technique. The characteristics of trailing vortex and its trajectory were described in detail for those three flow patterns. Since the space-resolution of PIV can only reach the sub-grid rather than the Kolmogorov scale, a large-eddy PIV analysis has been used to estimate the distribution of the turbulent kinetic energy dissipation. Comparison of the distributions of turbulent kinetic energy and dissipation rate in merging flow shows that the highest turbulent kinetic energy and dissipation are both located in the vortex regions, but the maxima are at somewhat different lo- cations behind the blade. About 37% of the total energy is dissipated in dual impeller jet flow regions. The obtained distribution of shear strain rate for merging flow is similar to that of turbulence dissipation, with the shear strain rate around the trailing vortices much higher than in other areas.

A Joint Delay-and-Sum and Fourier Beamforming Method for High Frame Rate Ultrasound Imaging

Frame rate is an important metric for ultrasound imaging systems,and high frame rates(HFR)benefit moving-target imaging.One common way to obtain HFR imaging is to transmit a plane wave.Delay-and-sum(DAS)beamformer is a conventional beamforming algorithm,which is simple and has been widely implemented in clinical application.Fourier beamforming is an alternative method for HFR imaging and has high levels of imaging efficiency,imaging speed,and good temporal dynamic characteristics.Nevertheless,the resolution and contrast performance of HFR imaging based on DAS or Fourier beamforming are insufficient due to the single plane wave transmission.To address this problem,a joint DAS and Fourier beamforming method is introduced in this study.The proposed method considers the different distributions of sidelobes in DAS imaging and Fourier imaging and combines the angular spectrum and DAS to reconstruct ultrasound images.The proposed method is evaluated on simulation and experimental phantom datasets to compare its performance with DAS and Fourier beamforming methods.Results demonstrate that the proposed method improves image effective dynamic range and resolution while also retaining a high frame rate of the ultrasound imaging systems.The proposed method improves the effective dynamic range along axial and lateral directions by 10 dB,compared to standard DAS and Fourier beamforming.

More efficient ground truth ROI image coding technique: implementation and wavelet based application analysis

In this paper, more efficient, low-complexity and reliable region of interest （ROI） image codec for compressing smooth low texture remote sensing images is proposed. We explore the efficiency of the modified RO! codec with respect to the selected set of convenient wavelet filters, which is a novel method. Such ROI coding experiment analysis representing low bit rate lossy to high quality lossless reconstruction with timing analysis is useful for improving remote sensing ground truth surveillance efficiency in terms of time and quality. The subjective [i.e. fair, five observer （HVS） evaluations using enhanced 3D picture view Hyper memory display technology] and the objective results revealed that for faster ground truth ROI coding applications, the Symlet-4 adaptation performs better than Biorthogonal 4.4 and Biorthogonal 6.8. However, the discrete Meyer wavelet adaptation is the best solution for delayed ROI image reconstructions.

Edge Oriented Compression Coding on Image Sequence

An edge oriented image sequence coding scheme is presented. On the basis of edge detecting, an image could be divided into the sensitized region and the smooth region. In this scheme, the architecture of sensitized region is approximated with linear type of segments. Then a rectangle belt is constructed for each segment. Finally, the gray value distribution in the region is fitted by normal forms polynomials. The model matching and motion analysis are also based on the architecture of sensitized region. For the smooth region we use the run length scanning and linear approximating. By means of normal forms polynomial fitting and motion prediction by matching, the images are compressed. It is shown through the simulations that the subjective quality of reconstructed picture is excellent at 0.0075 bit per pel.

Modeling the photon counting and photoelectron counting characteristics of quanta image sensors

A signal chain model of single-bit and multi-bit quanta image sensors(QISs)is established.Based on the proposed model,the photoresponse characteristics and signal error rates of QISs are investigated,and the effects of bit depth,quantum efficiency,dark current,and read noise on them are analyzed.When the signal error rates towards photons and photoelectrons counting are lower than 0.01,the high accuracy photon and photoelectron counting exposure ranges are determined.Furthermore,an optimization method of integration time to ensure that the QIS works in these high accuracy exposure ranges is presented.The trade-offs between pixel area,the mean value of incident photons,and integration time under different illuminance level are analyzed.For the 3-bit QIS with 0.16 e-/s dark current and 0.21 e-r.m.s.read noise,when the illuminance level and pixel area are 1 lux and 1.21μm^(2),or 10000 lux and 0.21μm^(2),the recommended integration time is 8.8 to 30 ms,or 10 to21.3μs,respectively.The proposed method can guide the design and operation of single-bit and multi-bit QISs.

Efficacy of image-enhanced endoscopy for colorectal adenoma detection:A multicenter,randomized trial

BACKGROUND Improved adenoma detection at colonoscopy has decreased the risk of developing colorectal cancer.However,whether image-enhanced endoscopy(IEE)further improves the adenoma detection rate(ADR)is controversial.AIM To compare IEE with white-light imaging(WLI)endoscopy for the detection and identification of colorectal adenoma.METHODS This was a multicenter,randomized,controlled trial.Participants were enrolled between September 2019 to April 2021 from 4 hospital in China.Patients were randomly assigned to an IEE group with WLI on entry and IEE on withdrawal(n=2113)or a WLI group with WLI on both entry and withdrawal(n=2098).The primary outcome was the ADR.The secondary endpoints were the polyp detection rate(PDR),adenomas per colonoscopy,adenomas per positive colonoscopy,and factors related to adenoma detection.RESULTS A total of 4211 patients(966 adenomas)were included in the analysis(mean age,56.7 years,47.1%male).There were 2113 patients(508 adenomas)in the IEE group and 2098 patients(458 adenomas)in the WLI group.The ADR in two group were not significantly different[24.0%vs 21.8%,1.10,95%confidence interval(CI):0.99-1.23,P=0.09].The PDR was higher with IEE group(41.7%)than with WLI group(36.1%,1.16,95%CI:1.07-1.25,P=0.01).Differences in mean withdrawal time(7.90±3.42 min vs 7.85±3.47 min,P=0.30)and adenomas per colonoscopy(0.33±0.68 vs 0.28±0.62,P=0.06)were not significant.Subgroup analysis found that with narrowband imaging(NBI),between-group differences in the ADR,were not significant(23.7%vs 21.8%,1.09,95%CI:0.97-1.22,P=0.15),but were greater with linked color imaging(30.9%vs 21.8%,1.42,95%CI:1.04-1.93,P=0.04).the second-generation NBI(2G-NBI)had an advantage of ADR than both WLI and the first-generation NBI(27.0%vs 21.8%,P=0.01;27.0%vs 21.2.0%,P=0.01).CONCLUSION This prospective study confirmed that,among Chinese,IEE didn’t increase the ADR compared with WLI,but 2G-NBI increase the ADR.

An Efficient Algorithm Based on Spectrum Migration for High Frame Rate Ultrasound Imaging

The high frame rate(HFR)imaging technique requires only one emission event for imaging.Therefore,it can achieve ultrafast imaging with frame rates up to the kHz regime,which satisfies the frame rate requirements for imaging moving tissues in scientific research and clinics.Lu’s Fourier migration method is based on a non-diffraction beam to obtain HFR images and can improve computational speed and efficiency.However,in order to obtain high-quality images,Fourier migration needs to make full use of the spectrum of echo signals for imaging,which requires a large number of Fast Fourier Transform(FFT)points and increases the complexity of the hardware when the echo frequency is high.Here,an efficient algorithm using the spectrum migration technique based on the spectrum’s distribution characteristics is proposed to improve the imaging efficiency in HFR imaging.Since the actual echo signal spectrum is of limited bandwidth,low-frequency and high-frequency parts with low-energy have little contribution to the imaging spectrum.We transform the effective part that provides the main energy in the signal spectrum to the imaging spectrum while the ineffective spectrum components are not utilized for imaging.This can significantly reduce the number of Fourier transform points,improve Fourier imaging efficiency,and ensure the imaging quality.The proposed method is evaluated on simulated and experimental datasets.Results demonstrated that the proposed method could achieve equivalent image quality with a reduced point number for FFT compared to the complete spectrum migration.In this paper,it only requires a quarter of the FFT points used in the complete spectrum migration,which can improve the computational efficiency;thus,it is more suitable for real-time data processing.The proposed spectrum migration method has a specific significance for the study and clinical application of HFR imaging.

Gender Recognition with Face Images Based on Partially Connected Neural Evolutionary

In this paper,a new type of neural network model - Partially Connected Neural Evolutionary (PARCONE) was introduced to recognize a face gender. The neural network has a mesh structure in which each neuron didn't connect to all other neurons but maintain a fixed number of connections with other neurons. In training,the evolutionary computation method was used to improve the neural network performance by change the connection neurons and its connection weights. With this new model,no feature extraction is needed and all of the pixels of a sample image can be used as the inputs of the neural network. The gender recognition experiment was made on 490 face images (245 females and 245 males from Color FERET database),which include not only frontal faces but also the faces rotated from-40°-40° in the direction of horizontal. After 300-600 generations' evolution,the gender recognition rate,rejection rate and error rate of the positive examples respectively are 96.2%,1.1%,and 2.7%. Furthermore,a large-scale GPU parallel computing method was used to accelerate neural network training. The experimental results show that the new neural model has a better pattern recognition ability and may be applied to many other pattern recognitions which need a large amount of input information.

Reconstruction and transmission of astronomical image based on compressed sensing

In the process of image transmission, the famous JPEG and JPEG-2000 compression methods need more transmission time as it is difficult for them to compress the image with a low compression rate. Recently the compressed sensing（CS） theory was proposed, which has earned great concern as it can compress an image with a low compression rate, meanwhile the original image can be perfectly reconstructed from only a few compressed data. The CS theory is used to transmit the high resolution astronomical image and build the simulation environment where there is communication between the satellite and the Earth. Number experimental results show that the CS theory can effectively reduce the image transmission and reconstruction time. Even with a very low compression rate, it still can recover a higher quality astronomical image than JPEG and JPEG-2000 compression methods.

An investigation on dissolution kinetics of single sodium carbonate particle with image analysis method

Dissolution kinetics of sodium carbonate is investigated with the image analysis method at the approach of single particle.The dissolution experiments are carried out in an aqueous solution under a series of controlled temperature and p H.The selected sodium carbonate particles are all spherical with the same mass and diameter.The dissolution process is quantified with the measurement of particle diameter from dissolution images.The concentration of dissolved sodium carbonate in solvent is calculated with the measured diameter of particle.Both surface reaction model and mass transport model are implemented to determine the dissolution mechanism and quantify the dissolution rate constant at each experimental condition.According to the fitting results with both two models,it is clarified that the dissolution process at the increasing temperature is controlled by the mass transport of dissolved sodium carbonate travelling from particle surface into solvent.The dissolution process at the increasing pH is controlled by the chemical reaction on particle surface.Furthermore,the dissolution rate constant for each single spherical sodium carbonate particle is quantified and the results show that the dissolution rate constant of single spherical sodium carbonate increases significantly with the rising of temperature,but decreases with the increasing of pH conversely.

A STUDY OF HIGH FRAME RATE ULTRASONIC IMAGING WITH LIMITED DIFFRACTION BEAMS

Objective To investigate a new class of solutions to the isotropic/homogeneous scalar wave equation, which termed limited diffraction beams and realize ultrasonic 3D imaging. Methods Limited diffraction beams were derived. We performed the study of 3D pulse echo imaging with limited diffraction array beam. To obtain high frame rate images, a single plane wave pulse (broadband) was transmitted with the arrays. Echoes received with the same arrays were processed with Fourier method to construct 3D images. Results Compared with traditional pulse echo imaging, this method has a larger depth of field, high frame rate, and high signal to noise ratio. Conclusion The new method has prospect of high frame rate 3D imaging. In addition, the imaging system based this method is easily implemented and has high quality image.

Method for Obtaining Line-of-Sight Rate with a Strap-down Imaging Guidance

In the strap-down TV guidance system, the line-of-sight（LOS） rate can not be obtained frora the measured information, the math platform to select missile attitude information must be set up. The LOS rate selecting models based on the missile attitude angle and the rate gyro are set up, the influencing factor and the extracting precision of LOS rate are emulated and analyzed.

Distortion-Free Data Embedding Scheme for High Dynamic Range Images

Distortion-free data embedding is a technique which can assure that not only the secret data is correctly extracted but also the cover media is recovered without any distortion after secret data is extracted completely. Because of these advantages, this technique attracts the attention of many researchers. In this paper, a new distortion-free data embedding scheme for high dynamic range （HDR） images is proposed. By depending on Cartesian product, this scheme can obtain higher embedding capacity while maintaining the exactly identical cover image and stego image when using the tone mapping algorithms. In experimental results, the proposed scheme is superior to Yu et aL＇s scheme in regard to the embedding rate——an average embedding rate of 0.1355 bpp compared with Yn et aL＇s scheme （0.1270 bpp）.

Research on Face Anti-Spoofing Algorithm Based on Image Fusion

Along with the rapid development of biometric authentication technology,face recognition has been commercially used in many industries in recent years.However,it cannot be ignored that face recognition-based authentication techniques can be easily spoofed using various types of attacks such photographs,videos or forged 3D masks.In order to solve this problem,this work proposed a face anti-fraud algorithm based on the fusion of thermal infrared images and visible light images.The normal temperature distribution of the human face is stable and characteristic,and the important physiological information of the human body can be observed by the infrared thermal images.Therefore,based on the thermal infrared image,the pixel value of the pulse sensitive area of the human face is collected,and the human heart rate signal is detected to distinguish between real faces and spoofing faces.In order to better obtain the texture features of the face,an image fusion algorithm based on DTCWT and the improved Roberts algorithm is proposed.Firstly,DTCWT is used to decompose the thermal infrared image and visible light image of the face to obtain high-and low-frequency subbands.Then,the method based on region energy and the improved Roberts algorithm are then used to fuse the coefficients of the high-and low-frequency subbands.Finally,the DTCWT inverse transform is used to obtain the fused image containing the facial texture features.Face recognition is carried out on the fused image to realize identity authentication.Experimental results show that this algorithm can effectively resist attacks from photos,videos or masks.Compared with the use of visible light images alone for face recognition,this algorithm has higher recognition accuracy and better robustness.

Atrous Convolution-Based Residual Deep CNN for Image Dehazing with Spider Monkey-Particle Swarm Optimization

Image dehazing is a rapidly progressing research concept to enhance image contrast and resolution in computer vision applications.Owing to severe air dispersion,fog,and haze over the environment,hazy images pose specific challenges during information retrieval.With the advances in the learning theory,most of the learning-based techniques,in particular,deep neural networks are used for single-image dehazing.The existing approaches are extremely computationally complex,and the dehazed images are suffered from color distortion caused by the over-saturation and pseudo-shadow phenomenon.However,the slow convergence rate during training and haze residual is the two demerits in the conventional image dehazing networks.This article proposes a new architecture“Atrous Convolution-based Residual Deep Convolutional Neural Network(CNN)”method with hybrid Spider Monkey-Particle Swarm Optimization for image dehazing.The large receptive field of atrous convolution extracts the global contextual information.The swarm based hybrid optimization is designed for tuning the neural network parameters during training.The experiments over the standard synthetic dataset images used in the proposed network recover clear output images free from distortion and halo effects.It is observed from the statistical analysis that Mean Square Error(MSE)decreases from 74.42 to 62.03 and Peak Signal to Noise Ratio(PSNR)increases from 22.53 to 28.82.The proposed method with hybrid optimization algorithm demonstrates a superior convergence rate and is a more robust than the current state-of-the-art techniques.