Convolutional neural network is widely used in image fusion. However, the deep learning framework is only applied in some part of the fusion process in most existing methods. To generate a full end-to-end image fusion pipeline, a Yshaped Generator model based on Generative Adversarial Network for infrared and visible image fusion is proposed. The idea of this method is to establish an adversarial game between the generator and the discriminator. The generator consisting of two Pyramid networks and three convolutional layers works as an autoencoder to improve the characteristic information of the fused images. As for the discriminator, it adopts a network structure similar to the Visual Geometry Group (VGG) network. The loss function uses the ratio loss to control the trade-off among generation loss and reconstruction loss. Results on publicly available datasets demonstrate that our method can improve the quality of detail information and sharpen the edge of infrared targets.
Aiming at the threats to spacecraft safety caused by space debris, and improving the stability and working life of spacecraft in orbit, it is proposed to use spacecraft equipped with a safety self-perceptual optical payload to detect space debris to improve the safety of the aircraft in orbit. This paper analyses the application methods and characteristics of the safety self-perceptual optical payload of space vehicles, and defines the technical indicators of the optical payload. The safety self-Perceptual optical payload includes the MWIR optical system with large field of view and the visible continuous zoom lens with large zoom ratio. The detector resolution is 1280×1024, the pixel size is 15μm, the focal length is 8mm, the F number is 2, and the field of view is 97.6°×85° of MWIR optical system;The detector resolution is 1920×1080, the pixel size is 5.5μm, the focal length is 15mm~750mm, which has a 50 times zoom ratio, and the field of view is 38.8°×22.4°~0.80°×0.45° of the visible continuous zoom lens. The two systems are athermal designed in the temperature range of -40°C~60°C respectively to meet the environmental requirements of space applications. Safety self-perceptual optical payload could obtain, and apperceive long-range targets in the 10km range around the space vehicle, and improve the aircraft's survival ability
With the development of infrared surveillance technology, the short focus zoom LWIR lens has been paid to more and more attention. In this paper, dual fields zoom lens with the fields of 20°×25°/8°×10° are designed by two different methods. The main specifications of the lens include: aperture is 1 / 2, detector resolution is 640 × 512, pixel size is 15 μ m, temperature adaptability is -40 ° to + 60 °. And we compare the volume, weight, imaging transmission, transmissivity and economy of the lens by different methods. It is found that the re-imaging method has smaller volume, weight and economy. While another imaging method has better transmittance, so the imaging system can reach higher noise equivalent power at the same image quality
KEYWORDS: 3D metrology, 3D modeling, 3D image processing, 3D acquisition, 3D image reconstruction, Image processing, 3D vision, Statistical methods, Statistical analysis
Measurement of 3D scene from image sequences is necessary for many computer vision applications. In this paper, we identify the volumetric scene reconstruction as a critical issue for target measurement and use the statistical method to estimate the size of the reconstructed target. The proposed approach unifies the view volume in volumetric scene reconstruction while we only know the location information of the camera relative to the target in elliptical orbit. Experimental results on elliptical orbit with 200 meters long axis and 100 meters short axis illustrate that the average error is about 44 millimeters, which meets the accuracy requirement of general measurement.
The traditional tone mapping algorithm for the display of high dynamic range (HDR) image has the drawback of losing the impression of brightness, contrast and color information. To overcome this phenomenon, we propose a new tone mapping algorithm based on dividing the image into different exposure regions in this paper. Firstly, the over-exposure region is determined using the Local Binary Pattern information of HDR image. Then, based on the peak and average gray of the histogram, the under-exposure and normal-exposure region of HDR image are selected separately. Finally, the different exposure regions are mapped by differentiated tone mapping methods to get the final result. The experiment results show that the proposed algorithm achieve the better performance both in visual quality and objective contrast criterion than other algorithms.
Gamma correction is a necessary operation for a digital image before it is sent to display. Uneven illumination images have low resolution and a lot of information is covered. In order to better removal of light effects and reproduce truly plain circumstances, this paper presents a new local adaptive gamma correction method. The experiment shows this method makes the brightness distribution more uniform and proved that the method compared with other methods that have better correction results.
Radiometric calibration is an important part for space remote sensing camera to obtain an accurate radiation value of ground target. The main significance of radiometric calibration is to reduce the influence by external scene and internal parameters of camera and to recover the real radiation property of objects. In order to break the limitation of line array imaging sensor, we propose a radiometric calibration method based on camera state matrix for area array camera. According to camera response characteristics, calculate and fit a functional relationship between the input radiance energy and the output digital number. Meanwhile, analyse and describe the procedure of radiometric calibration in detail. Experimental results indicates that the calibration method can provide high accuracy linear fitting parameters and can be widely applied to a large variety digital imaging systems.
Color constancy is an important problem in machine vision and image processing fields. We propose a new method in this paper that is based on detail information description to estimate the chromaticity of the light source and restore the real color property of captured images. The main idea of the proposed approach is that according to human vision characteristics use the interest information in an image to estimate the lighting condition of real scene. To approve the proposed method, two well-known algorithms are selected and their contrast results are also presented. It is shown in this paper that the proposed approach performs better than other traditional methods for color constancy most of the time.
Camera calibration is one of the essential steps in the computer vision research. This paper describes a real-time OpenCV based camera calibration system, and developed and implemented in the VS2008 environment. Experimental results prove that the system to achieve a simple and fast camera calibration, compared with MATLAB, higher precision and does not need manual intervention, and can be widely used in various computer vision system.
Color constancy performs an important role in computer vision and digital color image processing. The traditional color regulation algorithms which are based on the gray world assumption neglect the correlation between the three stimulus color components and the nonlinear effect between the different gray levels. In this paper, we propose a novel color constancy algorithm which is based on gray-curve regulation. The proposed algorithm first divides the luminance interval into several parts and then regulates the gray-curves of RGB three channels in each subinterval which can solve the correlation and nonlinear problems simultaneously. The experiment results show the effectiveness of the proposed algorithm.
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