Aiming at the problem of image quality degradation caused by the scattering of particles in the atmosphere under foggy conditions, a polarization dehazing algorithm combining the target polarization degree and atmospheric transmission model is proposed in this paper. Firstly, a bilateral filtering method combined with image gradient information is proposed to solve four target light intensity images from different angles, and the filtered images are used to solve the polarization degree of the target. This method can preserve the edge texture information of the target in the filtering process and effectively improve the quality of the reconstructed image. Secondly, when estimating the atmospheric light intensity at infinite distance, an alpha filtering method combined with bright channels is proposed to avoid the interference of over-bright noise points in the image. The method can effectively suppress the atmospheric light intensity at infinite distance. By analyzing the experimental data, the average gradient and gray variance of the fog-free reconstructed image are significantly improved compared with the original image. Experimental results show that the proposed algorithm has strong defogging ability, and can effectively improve the image quality of the optical imaging system in foggy scenes, and realize the restoration of
To solve the problem of poor sample diversity of infrared ship image data, a method of infrared ship image data expansion is implemented based on CycleGAN. The method using the ideas of circulating, iterative approximation, there can be no noise of ship target infrared simulation image dataset maps to conform to the actual infrared detection scenario of ship target image dataset, according to the demand of the subsequent target detection identification, on the premise of the ship target itself form unchanged, injected with appropriate clutter interference, so as to realize the effective expansion of the image data, the method fully considers the target and background infrared characteristics, and are not influenced by whether the scale of the target alignment issues, which can effectively increase the image sample of diversification, for subsequent ship target detection identification algorithm, provides rich data support. The comparison experiment of image structure similarity and object detection accuracy verifies the effectiveness of the algorithm.
The polarization phenomenon of the surface of an object and its changing in different spectra include its surface spatial geometric information and material information. Based on Kirchhoff law and Jones vector , the polarization model of the emission and reflection on the surface of the object is established, and the polarization phenomenon in infrared(IR) and visible light with different materials and incident angles are simulated. The IR and visible binocular polarization imaging system was constructed and the actual polarization data of small unmanned aerial vehicle(SUAV) and buildings were obtained. Two types of characteristic parameters, the degree of polarization and the angle of polarization, were extracted and analyzed, and the results proved that the SUAV and the background of the buildings had obvious differences in IR and visible. This research provides a basis for SUAV target detection and tracking using IR and visible polarization imaging in complex backgrounds.
Infrared polarization results from infrared-emitted radiation and reflected radiation effects. Polarization generated by infrared reflection is perpendicularly polarized, whereas polarization generated by infrared emission is parallelly polarized. Using the polarization feature in different directions can enhance the detection and discrimination of the target. Based on the Stokes vector, the polarization degree and angle are obtained. Then, according to the analysis of the polarization states, an orthogonality difference method of extracting polarization features is proposed. An infrared intensity and polarization feature images are fused using an algorithm of nonsubsampled shearlets transformation. Image evaluation indices of the target contrast to background (C), average gradient (AG), and image entropy (E) are employed to evaluate the fused image and original intensity image. Results demonstrate that every index of the fused image with the polarization feature is significantly improved, thereby validating the effectiveness of the proposed target-enhancement approach using polarization features extracted by the orthogonal difference method.
A method of feature extraction and small target detection, based on infrared polarization, which uses the technical superiority of infrared polarization imaging in artificial target detection to solve the clutter interference problem in infrared target detection, is proposed. First, using the differences in the polarization characteristics of the artificial target and the natural background, the infrared polarization information models for the target and background are established. The compositions of intensity information, polarization information, and target polarization information are extracted, and enhancement measures are analyzed. Then, the variable polarization theories are combined to extract the target polarization characteristics and suppress the background clutter. Finally, the infrared small target is detected, and comparisons with existing methods demonstrate the effectiveness and reliability of the proposed method.
In the infrared small target detection system, CFAR (Constant False Alarm Rate) is a commonly used technology, but in the traditional single frame detection method, detection rate is requested to be improved while the false alarm rate is increasing. This paper proposes a threshold attenuation CFAR detection method based on Gauss distribution. After the preprocessing of infrared images, we came into the designing of CFAR detector based on Gauss distribution. According to the previous frame target location and attenuation of local threshold, the detection rate of the target neighbourhood can be improved to obtain the current target location. The experimental results show that the proposed method can effectively control the threshold, and under the precondition that the background clutter was suppressed by the global low false alarm rate, it can improve the local detection rate and reduce the probability of target loss.
In this paper, through analyzing the derivation process and computer simulations, we find that the update formulas for
PHD-TBD filter in paper [5] are somewhat unreasonably. When using the paper’s PHD update formula, the targets’ state
parameters cannot be estimated. Following the method in paper 2, we treat the objects to be detected in TBD situations
as special extended targets and derive a new PHD-TBD update formula analytically under this assumption. The
correctness of the derivation is validated by computer simulations.
Infrared polarization imaging is a new kind of infrared detection technology developed in recent ten years. Different
from the traditional detection method of infrared imaging, infrared polarization imaging can not only obtain infrared
radiation intensity information of targets, but also obtain the infrared radiation polarization information. So the
polarization of the target scene is the physical basis of infrared polarization imaging detection.
On the basis of the research about infrared polarization imaging theory, the characteristics of long-wave infrared
polarization detection was analyzed in this paper. Firstly, the paper studied long-wave infrared polarization state and
interaction effect which coming from the spontaneous emission of target and environment, then designed the analysis
experiment about long-wave infrared polarization characteristics that coming from spontaneous radiation, further and
verified the forming mechanism of long wave infrared polarization. Through the several experiments that the long wave
polarization information of different material objects being measured, a physical phenomenon was found that with the
long-wave thermal radiation transmitting form high temperature object to low temperature object, the polarization
characteristics transfer process had been happened at the same time, and the degree of this transfer was associated with
the material and self-temperature of the objects.
KEYWORDS: Laser range finders, Spherical lenses, 3D image processing, 3D modeling, Object recognition, Principal component analysis, Data modeling, Feature extraction, Error analysis, Lithium
The description of local surface features is a critical step in surface matching and object recognition. We present a descriptor for three-dimensional shapes based on the bispectrum of spherical harmonics (BSH). First, points in a support region of a feature point are used to construct a local reference frame, and a histogram is formed by accumulating the points falling within each bin in the support region. Second, spherical harmonic coefficients of the histogram and its bispectrum are calculated. Finally, the feature descriptor is obtained via principal component analysis. We tested our BSH descriptor on public datasets and compared its performance with that of several existing methods. The results of our experiments show that the proposed descriptor outperforms other methods under various noise levels and mesh resolutions.
In this paper, by using the theoretical analysis and computer simulation method, the lower boundary requirements of the infrared imaging sensor are analyzed when detecting the thermal surface features of the wake behind a moving underwater body. Firstly, the computer simulation model of the underwater body wake’s surface temperature field and the corresponding surface infrared features are established. Secondly, the measures of the sensor’s detection performance and the computation method of these measures are described. Thirdly, by using the infrared features’ simulation model and the performance measures, we have done simulation tests to analyze the given infrared imaging sensor’s detection ability for detecting underwater body wake, and the requirements of infrared sensor to detect the wake’s infrared surface feature under some given working states are also investigated. Lastly, the simulation results and the conclusions of the paper are given. The problem-solving flow chart and the simulation results on underwater object wake’s detectability given in this paper may be useful for the designment and performance evaluation of the infrared imaging sensors.
Infrared small target detection is a crucial and yet still is a difficult issue in aeronautic and astronautic applications. Sparse representation is an important mathematic tool and has been used extensively in image processing in recent years. Joint sparse representation is applied in dual-band infrared dim target detection in this paper. Firstly, according to the characters of dim targets in dual-band infrared images, 2-dimension Gaussian intensity model was used to construct target dictionary, then the dictionary was classified into different sub-classes according to different positions of Gaussian function’s center point in image block; The fact that dual-band small targets detection can use the same dictionary and the sparsity doesn’t lie in atom-level but in sub-class level was utilized, hence the detection of targets in dual-band infrared images was converted to be a joint dynamic sparse representation problem. And the dynamic active sets were used to describe the sparse constraint of coefficients. Two modified sparsity concentration index (SCI) criteria was proposed to evaluate whether targets exist in the images. In experiments, it shows that the proposed algorithm can achieve better detecting performance and dual-band detection is much more robust to noise compared with single-band detection. Moreover, the proposed method can be expanded to multi-spectrum small target detection.
KEYWORDS: Temperature metrology, Black bodies, Infrared radiation, Signal attenuation, Distortion, Pyrometry, Infrared imaging, Rockets, Missiles, Signal detection
Temperature is an important feature of infrared targets. However, due to the attenuation and distortion parameters in radiation transmission process are unknown, precise temperature measurement is a difficult task. In this paper, a modified Dual-Band Ratio (DBR) temperature measurement method for remote target is proposed. The method is based on a new presented variation derived from the temperature change process named Dual-Band Differential Ratio (DBDR). Firstly, the temperature of the target is estimated by the traditional DBR method, and then a correction using DBDR information is carried out to improve the measurement accuracy. Experiment results showed that the proposed method can improve the temperature measurement accuracy and it could also be carried out without any prior information about the target.
KEYWORDS: LIDAR, Computer simulations, Detection and tracking algorithms, Optical simulations, 3D acquisition, 3D image processing, 3D modeling, Image processing, Motion models, Signal processing
Scanning Laser Radar has been widely used in many military and civil areas. Usually there are relative movements between the target and the radar, so the moving target image modeling and simulation is an important research content in the field of signal processing and system design of scan-imaging laser radar. In order to improve the simulation speed and hold the accuracy of the image simulation simultaneously, a novel fast simulation algorithm is proposed in this paper. Firstly, for moving target or varying scene, an inequation that can judge the intersection relations between the pixel and target bins is obtained by deriving the projection of target motion trajectories on the image plane. Then, by utilizing the time subdivision and approximate treatments, the potential intersection relations of pixel and target bins are determined. Finally, the goal of reducing the number of intersection operations could be achieved by testing all the potential relations and finding which of them is real intersection. To test the method’s performance, we perform computer simulations of both the new proposed algorithm and a literature’s algorithm for six targets. The simulation results show that the two algorithm yield the same imaging result, whereas the number of intersection operations of former is equivalent to only 1% of the latter, and the calculation efficiency increases a hundredfold. The novel simulation acceleration idea can be applied extensively in other more complex application environments and provide equally acceleration effect. It is very suitable for the case to produce a great large number of laser radar images.
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