Adaptive Window Based 3-D Feature Selection for Multispectral Image Classification Using Firefly Algorithm

Feature extraction is the most critical step in classification of multispectral image.The classification accuracy is mainly influenced by the feature sets that are selected to classify the image.In the past,handcrafted feature sets are used which are not adaptive for different image domains.To overcome this,an evolu-tionary learning method is developed to automatically learn the spatial-spectral features for classification.A modified Firefly Algorithm(FA)which achieves maximum classification accuracy with reduced size of feature set is proposed to gain the interest of feature selection for this purpose.For extracting the most effi-cient features from the data set,we have used 3-D discrete wavelet transform which decompose the multispectral image in all three dimensions.For selecting spatial and spectral features we have studied three different approaches namely overlapping window(OW-3DFS),non-overlapping window(NW-3DFS)adaptive window cube(AW-3DFS)and Pixel based technique.Fivefold Multiclass Support Vector Machine(MSVM)is used for classification purpose.Experiments con-ducted on Madurai LISS IV multispectral image exploited that the adaptive win-dow approach is used to increase the classification accuracy.

Sparse flight spotlight mode 3-D imaging of spaceborne SAR based on sparse spectrum and principal component analysis

The spaceborne synthetic aperture radar(SAR)sparse flight 3-D imaging technology through multiple observations of the cross-track direction is designed to form the cross-track equivalent aperture,and achieve the third dimensionality recognition.In this paper,combined with the actual triple star orbits,a sparse flight spaceborne SAR 3-D imaging method based on the sparse spectrum of interferometry and the principal component analysis(PCA)is presented.Firstly,interferometric processing is utilized to reach an effective sparse representation of radar images in the frequency domain.Secondly,as a method with simple principle and fast calculation,the PCA is introduced to extract the main features of the image spectrum according to its principal characteristics.Finally,the 3-D image can be obtained by inverse transformation of the reconstructed spectrum by the PCA.The simulation results of 4.84 km equivalent cross-track aperture and corresponding 1.78 m cross-track resolution verify the effective suppression of this method on high-frequency sidelobe noise introduced by sparse flight with a sparsity of 49%and random noise introduced by the receiver.Meanwhile,due to the influence of orbit distribution of the actual triple star orbits,the simulation results of the sparse flight with the 7-bit Barker code orbits are given as a comparison and reference to illuminate the significance of orbit distribution for this reconstruction results.This method has prospects for sparse flight 3-D imaging in high latitude areas for its short revisit period.

MONO-PULSE RADAR 3-D IMAGING TECHNIQUES FOR TARGET IN STEPPED TRACKING MODE

A method for mono-pulse radar 3-D imaging in stepped tracking mode is presented and the amplitude linear modulation of error signals in stepped tracking mode is analyzed with its compensation method followed, so the problem of precisely tracking of target is solved. Finally the validity of these methods is proven by the simulation results.

Spectrum Illumination for 3-D Surface Imaging System

A method using spectrum illumination to reconstruct 3-D object image is a new concept in the field of computer vision. The design of optical illumination system is crucial in this method. Several ways to achieve multi-color spectrum illumination are discussed. A prism illumination system is designed by means of aligning symmetrically the prism at the mid-wavelength (n d=1.806 274) of light path and using reflection collimating lens, cylindrical expending lens and two optical shutters. The relations between deviation angles and light wavelengths are given, and some 3-D reconstruction results are presented.

Digital Beamforming by Multiple Chirp Zeta Transforms for 3-D Sonar Imaging Systems

The computational load is prohibitive for real-time image generation in 3-D sonar systems, particularly when the steering angle approximation is required. In this paper, a novel multiple Chirp Zeta Transforms （MCZT） beamforming method in frequency domain is being proposed. The single long-length Chirp Zeta Transform （CZT） in the original CZT beamforming is replaced by several CZTs with smaller lengths for different partitions along each dimension. The implementing routine of the algorithm is also optimized. Furthermore, an avenue to evaluate the estimating error for the angle approximation in 3-D imaging applications is presented, and an approach to attain valid partitions for the steering angles is also flhistrated. This paper demonstrates a few advantages of the proposed frequency-domain beamforming method over existing methods in terms of the computatianal complexity.

Novel registration algorithm for 3-D images captured from multiple views of object surface

A novel algorithm of 3-D surface image registration is proposed. It makes use of the array information of 3-D points and takes vector/vertex-like features as the basis of the matching. That array information of 3-D points can be easily obtained when capturing original 3-D images. The iterative least-mean-squared （LMS） algorithm is applied to optimizing adaptively the transformation matrix parameters. These can effectively improve the registration performance and hurry up the matching process. Experimental results show that it can reach a good subjective impression on aligned 3-D images. Although the algorithm focuses primarily on the human head model, it can also be used for other objects with small modifications.

Monitoring slope deformation using a 3-D laser image scanning system: a case study

An ILRIS-36D 3-D laser image scanning system was used to monitor the Anjialing strip mine slope on Pingshuo in Shanxi province. The basic working principles, performance indexes, features and data collection and processing methods are illus-trated. The point cloud results are analyzed in detail. The rescale range analysis method was used to analyze the deformation char-acteristics of the slope. The results show that the trend of slope displacement is stable and that the degree of landslide danger is low. This work indicates that 3-D laser image scanning can supply multi-parameter, high precision real time data over long distances. These data can be used to study the distortion of the slope quickly and accurately.

RM-CSTV:An effective high-resolution method of non-line-of-sight millimeter-wave radar 3-D imaging

Non-line-of-sight(NLOS)imaging is a novel radar sensing technology that enables the reconstruction of hidden targets.However,it may suffer from synthetic aperture length reduction caused by ambient occlusion.In this study,a complex total variation(CTV)regularization-based sparse reconstruction method for NLOS three-dimensional(3-D)imaging by millimeter-wave(mm W)radar,named RM-CSTV method,is proposed to improve imaging quality and speed.In this scheme,the NLOS imaging model is first introduced,and associated geometric constraints for NLOS objects are established.Second,an effective high-resolution NLOS imaging method based on the range migration(RM)kernel and complex sparse joint total variation constraint,dubbed as modified RM-CSTV,is proposed for 3-D high-resolution imaging with edge information.The experiments with multi-type NLOS targets show that the proposed RM-CSTV method can provide effective and high-resolution NLOS targets 3-D imaging.

MULTI-SPECTRAL AND HYPERSPECTRAL IMAGE FUSION USING 3-D WAVELET TRANSFORM

Image fusion is performed between one band of multi-spectral image and two bands of hyperspectral image to produce fused image with the same spatial resolution as source multi-spectral image and the same spectral resolution as source hyperspeetral image. According to the characteristics and 3-Dimensional （3-D） feature analysis of multi-spectral and hyperspectral image data volume, the new fusion approach using 3-D wavelet based method is proposed. This approach is composed of four major procedures： Spatial and spectral resampling, 3-D wavelet transform, wavelet coefficient integration and 3-D inverse wavelet transform. Especially, a novel method, Ratio Image Based Spectral Resampling （RIBSR）method, is proposed to accomplish data resampling in spectral domain by utilizing the property of ratio image. And a new fusion rule, Average and Substitution （A＆S） rule, is employed as the fusion rule to accomplish wavelet coefficient integration. Experimental results illustrate that the fusion approach using 3-D wavelet transform can utilize both spatial and spectral characteristics of source images more adequately and produce fused image with higher quality and fewer artifacts than fusion approach using 2-D wavelet transform. It is also revealed that RIBSR method is capable of interpolating the missing data more effectively and correctly, and A＆S rule can integrate coefficients of source images in 3-D wavelet domain to preserve both spatial and spectral features of source images more properly.

A"messenger zone hypothesis"based on the visual three-dimensional spatial distribution of motoneurons innervating deep limb muscles

Coordinated contraction of skeletal muscles relies on selective connections between the muscles and multiple classes of the spinal motoneuro ns.Howeve r,current research on the spatial location of the spinal motoneurons innervating differe nt muscles is limited.In this study,we investigated the spatial distribution and relative position of different motoneurons that control the deep muscles of the mouse hindlimbs,which were innervated by the obturator nerve,femoral nerve,inferior gluteal nerve,deep pe roneal nerve,and tibial nerve.Locations were visualized by combining a multiplex retrograde tracking technique compatible with three-dimensional imaging of solvent-cleared o rgans(3DISCO)and 3-D imaging technology based on lightsheet fluorescence microscopy(LSFM).Additionally,we propose the hypothesis that"messenger zones"exist as interlaced areas between the motoneuron pools that dominate the synergistic or antagonist muscle groups.We hypothesize that these interlaced neurons may participate in muscle coordination as messenger neurons.Analysis revealed the precise mutual positional relationships among the many motoneurons that innervate different deep muscles of the mouse.Not only do these findings update and supplement our knowledge regarding the overall spatial layout of spinal motoneurons that control mouse limb muscles,but they also provide insights into the mechanisms through which muscle activity is coordinated and the architecture of motor circuits.

MODELING OF 3-D IMAGES AND SPACE MARKOV CUBIC MESH MODELS

Three-dimensional(3-D)Markov cubic random mesh models are presented andproved in the form of two theorems in details.Its applications to the modeling and description of3-D images are described.The model presented here is a appropriate mathematical tool for thesegmentation,modeling,classification and other processing.Finally,an example is given.

An Experimental System Development for Head Posture Estimation Based on 3-D Images Measurement

Although automobile is an indispensable vehicle to modern life, it also serves as a social problem with a big traffic accident. Among the reasons of traffic accidents, careless driving accounts for the largest part. So in order to avoid the careless driving, a system which can measure the posture of a driver and warns driver to drive carefully in the case of looking aside is necessary. Although the image measurement method is used broadly, there is a problem on which measurement accuracy is influenced by environment light, makeup of the driver, etc. in the general method based on the two-dimensional image. Therefore, in this study, we propose an image measurement method to obtain the head posture of driver. First we use three-dimensional measurement method which based on the infrared pattern projection to get 3-D information of head, and then we calculate the angle for faces. In this paper, we explain the composition method of an experiment system, and the results of head posture measurement experiment.

SAR tomography imaging via higher-order spectrum analysis

To deal with the non-Caussian noise in standard 2-D SAR images, the deramped signal in imaging plane, and the possible symmetric distribution of complex noise, the fourth-order cumulant of complex process is introduced into SAR tomography. With the estimated AR parameters of ARMA model of noise through Yule-Walker equation, the signal series of height is pre-filtered. Then, through ESPRIT, the spectrum is obtained and the aperture in height direction is synthesized. Finally, the SAR tomography imaging of scene is achieved. The results of processing on signal with non-Gaussian noise demonstrate the robustness of the proposed method. The tomography imaging of the scenes shows that the higher-order spectrum analysis is feasible in the application.

Imaging plaque inflammation in asymptomatic cocaine addicted individuals with simultaneous positron emission tomography/magnetic resonance imaging

BACKGROUND Chronic cocaine use is associated with stroke, coronary artery disease and myocardial infarction, resulting in severe impairments or sudden mortality. In the absence of clear cardiovascular symptoms, individuals with cocaine use disorder (iCUD) seeking addiction treatment receive mostly psychotherapy and psychiatric pharmacotherapy, with no attention to vascular disease (i.e., atherosclerosis). Little is known about the pre-clinical signs of cardiovascular risk in iCUD and early signs of vascular disease are undetected in this underserved population. AIM To assess inflammation, plaque burden and plaque composition in iCUD aiming to detect markers of atherosclerosis and vascular disease. METHODS The bilateral carotid arteries were imaged with positron emission tomography/magnetic resonance imaging (PET/MRI) in iCUD asymptomatic for cardiovascular disease, healthy controls, and individuals with cardiovascular risk. PET with 18F-fluorodeoxyglucose (18F-FDG) evaluated vascular inflammation and 3-D dark-blood MRI assessed plaque burden including wall area and thickness. Drug use and severity of addiction were assessed with standardized instruments. RESULTS The majority of iCUD and controls had carotid FDG-PET signal greater than 1.6 but lower than 3, indicating the presence of mild to moderate inflammation. However, the MRI measure of wall structure was thicker in iCUD as compared to the controls and cardiovascular risk group, indicating greater carotid plaque burden. iCUD had larger wall area as compared to the healthy controls but not as compared to the cardiovascular risk group, indicating structural wall similarities between the non-control study groups. In iCUD, wall area correlated with greater cocaine withdrawal and craving. CONCLUSION These preliminary results show markers of carotid artery disease burden in cardiovascular disease-asymptomatic iCUD. Broader trials are warranted to develop protocols for early detection of cardiovascular risk and preventive intervention in iCUD.

Comparison of Laboratory Measurements for IR Imaging System Performance

Sensitivity and human performance are two important parameters for IR imaging system. Noise equivalent temperature difference (NETD) and minimum resolvable temperature difference (MRTD) can describe sensitivity and human performance of IR imaging system. So a lot of engineers apply themselves to studying the methods to measure NETD and MRTD for IR imaging system. The classical laboratory measurement methodologies for NETD and MRTD are introduced. And, two new approaches to three-dimensional (3-D) noise and MRTD/MRC are also portrayed, which can overcome some of the disadvantages existed in classical testing of NETD and MRTD. With the help of the new laboratory measurements, the disadvantages of the classical methods to measure NETD and MRTD can be solved.

A TENSOR ANALYSIS METHOD FOR ESTIMATING 3-D MOTION PARAMETERS

By using the center projection image sequence to estimate 3-D motion parameters,one needs to know the corresponding relationship between the feature of motion object in spaceand the projection coordinate on image plane.In order to avoid using the relationship of featurecorrespondence,the tensor analysis method in the affine transformation system is presented,andthe simulation data of experimental results are given.

Linear Phase FIR Filter on Measuring 3-D Surface

An optical technology for 3-D surface measurement is set up.The technology,based on a deformed projected grating pattern which carries the 3-D information of the measured object,can automatically and accurately obtain the phase map of a measured object by using a linear-phase FIR filter.In contrast to the 2-D fast Fourier transform technique,it’s more than fast.Only one image pattern is sufficient for measuring.The phase map can be processed without assigning fringe orders and making distinction between a depression and an elevation.Theoretical analysis and experimental result are presented.

Experimental assessment of a 3-D plenoptic endoscopic imaging system

All endoscopic imaging system using a plenoptic technique to reconstruct 3-D information is demonstrated and analyzed in this Letter. The proposed setup integrates a clinical surgical endoscope with a plenoptic camera to achieve a depth accuracy error of about 1 mm and a precision error of about 2 mm, within a 25 mm×25 mm field of view, operating at 11 frames per second.

PC-BASED SURFACE RECONSTRUCTION OF MEDICAL CT IMAGES

It is an active research area to reconstruct 3-D object and display its visible surfacesfrom cross-sectional images. In this paper, the methods of reconstructing 3-D object from medicalCT images and displaying the visible surfaces are discussed. A polygon approximation methodthat forms polygon with the same number of segment points and a fast interpolation method forcross-sectional contours are presented at first. Then the voxel set of a human liver is reconstructed.And then the liver voxel set is displayed using depth and gradient shading methods. The softwareis written in C programming language at a microcomputer image processing system with a PC/ATcomputer as the host and a PC-VISION board as the image processing unit. The result of theprocessing is satisfying.

Multimodality image registration and fusion using neural network

Multimodality image registration and fusion are essential steps in building 3-D models from remotesensing data. We present in this paper a neural network technique for the registration and fusion of multimodali-ty remote sensing data for the reconstruction of 3-D models of terrain regions. A FeedForward neural network isused to fuse the intensity data sets with the spatial data set after learning its geometry. Results on real data arepresented. Human performance evaluation is assessed on several perceptual tests in order to evaluate the fusionresults.