New Method of Image Background Suppression Based on Soft Morphology and Retinex Theory

Abstract EN

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.