Abstract
A new river flow measurement method based on graphic process has been proposed recently, which gets the velocity in optical imaging modality through measuring the continuous displacement of floating debris, then reconstructs a two-dimensional river surface velocity field by using the velocity of floating debris, and computes the section flow at last. However, the surface optical images have not only lights of target information, but also surface optical noise. It is difficult for reliable and stable continuous displacement detection of complex small observation target, which occupies only a small number of pixels comparing to a large field imaging area and has complex optical reflection properties. To solve this problem, this paper presents a background suppression method based on soft morphology and Retinex theory. Soft morphology is firstly used for the opening operation of the image, and then Retinex theory is used for optimal estimation of image incident component to suppress background of image. Finally, the simulations show that our method is superior to gray morphology and soft morphology on the performance of targets enhancement, noise filtering, and background suppression, and it has better background and targets discrimination quality subjective evaluation and higher signal-to-clutter ratio.
Highlights
Image background suppression is the method of removing the relatively motionless background information from video frames and retaining the moving target information of a scene from video frames
In order to improve the background suppression effect of soft morphology, we propose a new background suppression method based on soft morphology filtering and Retinex theory
In order to verify the effectiveness of the proposed method, we make an experiment with the method which combines with soft morphological opening operation and optimal estimation of incident component with background suppression of the image based on Retinex theory
Summary
Image background suppression is the method of removing the relatively motionless background information from video frames and retaining the moving target information of a scene from video frames. The river flow measure method needs to capture images on the river bank of a tilt angle of the surface and measures large areas of natural rivers, gets the velocity in optical imaging modality through measuring the continuous displacement of floating debris such as tree branches, leaves, and other water tracers, reconstructs a two-dimensional river surface velocity field by using the velocity of floating debris, and computes the section flow by velocity-area method at last This measurement method was called large-scale particle image velocimetry [1,2,3,4,5,6,7,8] and has been applied widely in the field of hydrology. This paper will propose one new background suppression method of the river surface image based on soft morphology and optimal estimation of image incidence component in Retinex theory.
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