Abstract
For some measurement and detection applications based on video (sequence images), if the exposure time of camera is not suitable with the motion speed of the photographed target, fuzzy edges will be produced in the image, and some poor lighting condition will aggravate this edge blur phenomena. Especially, the existence of noise in industrial field environment makes the extraction of fuzzy edges become a more difficult problem when analyzing the posture of a high-speed moving target. Because noise and edge are always both the kind of high-frequency information, it is difficult to make trade-offs only by frequency bands. In this paper, a noise-tolerant edge detection method based on the correlation relationship between layers of wavelet transform coefficients is proposed. The goal of the paper is not to recover a clean image from a noisy observation, but to make a trade-off judgment for noise and edge signal directly according to the characteristics of wavelet transform coefficients, to realize the extraction of edge information from a noisy image directly. According to the wavelet coefficients tree and the Lipschitz exponent property of noise, the idea of neural network activation function is adopted to design the activation judgment method of wavelet coefficients. Then the significant wavelet coefficients can be retained. At the same time, the non-significant coefficients were removed according to the method of judgment of isolated coefficients. On the other hand, based on the design of Daubechies orthogonal compactly-supported wavelet filter, rational coefficients wavelet filters can be designed by increasing free variables. By reducing the vanishing moments of wavelet filters, more high-frequency information can be retained in the wavelet transform fields, which is benefit to the application of edge detection. For a noisy image of high-speed moving targets with fuzzy edges, by using the length 8-4 rational coefficients biorthogonal wavelet filters and the algorithm proposed in this paper, edge information could be detected clearly. Results of multiple groups of comparative experiments have shown that the edge detection effect of the proposed algorithm in this paper has the obvious superiority.
Highlights
IntroductionIts processing object is mainly digital video (sequence images), and studies the measurement and estimation of the structural or motion parameters of the moving target [2,3]
In recent years, the concept of video-metrics has been proposed [1]
In edge detection method basedbased on the on correlation relationship between
Summary
Its processing object is mainly digital video (sequence images), and studies the measurement and estimation of the structural or motion parameters of the moving target [2,3]. A high-speed visual measurement system captures the status change of the moving target at the transient time by using a high-speed camera, and instantaneously presents the information that cannot be captured by human eyes or other conventional sensors, in the form of continuous sequence images. Sensors 2019, 19, 343 measurement of high-speed moving target, research of collision transient, weak signal extraction, and vibration analysis [4,5,6]. In order to capture the high-speed moving target image, the camera is required to have a fast-enough exposure frequency. On the other hand, when the camera exposure time is too short, it needs to have enough light conditions to ensure the image quality, otherwise the image will be blurred due to insufficient light
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