Space Object Detection in Images Using Matched Filter Bank and Bayesian Update

Murphy, Timothy S.; Holzinger, Marcus J.; Flewelling, Brien

doi:10.2514/1.g001934

Cited by 15 publications

(3 citation statements)

References 26 publications

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“…Inspired by the 1 − D applications, researchers extended template object detection to image object manipulations. The applications in image processing includes texture discriminations and target object tracking [32], seismic imaging and event detections [33], [34], medical analysis [35]- [37], and feature extraction [38].…”

Section: B the Matched Filtering Of The Gabor Image Spacementioning

confidence: 99%

An Integrated Multiscale Geometric Analysis Approach for Automatic Extraction of Power Lines From High Resolution Remote Sensing Images

Feyissa

Cao

2020

IEEE Access

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High resolution remote sensing systems provide cheaper and fast way of acquiring images of power lines. However, such images depicting the details of other complex background objects, noises, and complicated brightness measurements, make separate extraction of the power lines challenging. This paper addresses the problem of automatic extraction of power lines from high resolution remote sensing images obtained from different sources. In order to automatically extract the power lines, we proposed an integrated Multiscale Geometric Analysis (MGA) approach. First, complementary Gabor and matched filters (MF) were employed over an image to suppress unnecessary background and noises, and initial discrimination of the power lines. Then, the filtering output was decomposed in to scale and orientation based subband coefficients using the Fast Discrete Curvelet Transform (FDCT) so as to access and modify different image features separately. By employing selective modification operations, well-established power line structures ready for extraction were derived. Finally the powerlines were extracted with hysteresis thresholding. The approach was successful in extracting power lines from high resolution images captured in any orientation. It is robust even when the source image is cluttered, and degraded due to noise and brightness effects. Power lines represented by weak intensities, crossing bright image regions, changing direction, closer power lines and those crossing each other, disconnected/broken power lines due to noise and occlusions were all inferred and extracted successfully. The approach was validated using real test images and the performance measures showed over 90% average accuracy fitting the ground truth.

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Section: B the Matched Filtering Of The Gabor Image Spacementioning

confidence: 99%

An Integrated Multiscale Geometric Analysis Approach for Automatic Extraction of Power Lines From High Resolution Remote Sensing Images

Feyissa

Cao

2020

IEEE Access

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“…Many experts have conducted research on target detection methods. For example, template matching method (Liu et al 2012;Murphy et al 2016), this type of algorithm is simple to calculate, but due to the uncertain size of the space target, the use of a single template will greatly reduce the detection accuracy of the algorithm. Morphological operator (Wei et al 2018), the detection effect of the algorithm usually depends on the selection of the structure operator.…”

Section: Introductionmentioning

confidence: 99%

Automatic Space Debris Extraction Channel Based on Large Field of view Photoelectric Detection System

Jiang¹,

Liu²,

Yang³

et al. 2022

PASP

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Space target detection is the core technology of space surveillance system. The large field of view telescope has strong space detection capabilities, and its realization also faces many challenges. We propose an automatic extraction algorithm for space debris, aiming to automatically extract information about space targets. Our method is mainly divided into three parts. In the first stage, image denoising processing is carried out for various noise interference in the image. The proposed wavelet transform and total variational hybrid filtering algorithm are applied to eliminate noise, which reduces the impact of noise on target detection and greatly retains target information. In the second stage, we propose an improved morphological operator to eliminate uneven background. The third stage uses Hough transform to obtain candidate debris targets. These images were taken during an observation campaign, the observatory is located in Jilin. Experimental results show that the target detection algorithm proposed in this paper can effectively extract space target information and solve the problem of space target detection for large-field telescopes.

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“…Therefore, many methods have been proposed to solve the problem of faint target detection in optical images. For example, template matching method (Liu et al 2012;Murphy et al 2016), morphological operator (Wei et al 2018), neural network (Jia et al 2020). Jiao proposed a method of combining high-level statistics and prediction.…”

Section: Introductionmentioning

confidence: 99%

Faint Space Debris Detection Algorithm Based on Small Aperture Telescope Detection System

Jiang¹,

Liu²,

Kang³

et al. 2022

Res. Astron. Astrophys.

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Ground-based photoelectric observation has unique advantages in space target observation. However, due to the weak light-gathering ability of small-aperture optoelectronic observation telescopes, the space debris in the image is weak and easily drowned in noise. In order to solve the above problems, we use digital image processing technology to extract faint space debris. We propose a high detection rate space debris automatic extraction algorithm, aiming to automatically detect space debris. We first establish a new space target description model. It is mainly divided into two stages. The purpose of the first stage is to reduce the influence of a large number of stars. A hybrid filtering of wavelet transform and guided filtering for three consecutive frames, and the reconstructed wavelet is taken the median value can achieve the effect of eliminating stars. In the second stage, we adopt the method of robust principal component analysis and attribute the problem of target detection to the problem of separating the target and background of a single frame of image. After a large number of experimental results analysis, it is proved that the algorithm can effectively detect weak debris in the monitoring system of small aperture telescope, and has high precision and low computational complexity.

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Space Object Detection in Images Using Matched Filter Bank and Bayesian Update

Cited by 15 publications

References 26 publications

An Integrated Multiscale Geometric Analysis Approach for Automatic Extraction of Power Lines From High Resolution Remote Sensing Images

An Integrated Multiscale Geometric Analysis Approach for Automatic Extraction of Power Lines From High Resolution Remote Sensing Images

Automatic Space Debris Extraction Channel Based on Large Field of view Photoelectric Detection System

Faint Space Debris Detection Algorithm Based on Small Aperture Telescope Detection System

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