Sea surface object image background inhibition method based on convolution nerve network

Abstract

The invention discloses a sea surface object image background inhibition method based on a convolution nerve network, comprising steps of choosing imaging data of a sea surface object under a complex scene, performing pre-processing on the imaging data and then dividing the imaging data into a training set L1 and a verification set L2 according to a certain proportion; using a training set L1 to train the convolution nerve network, using a verification set L2 to perform optimization regulation on a network model to obtain a background prediction model B-Mod; performing pre-processing on the sea surface target image to be inhibited and then inputting the background prediction model B-Mod, and calculating a background inhibition component of each pixel; adding and averaging all the background inhibition components of each pixel to obtain a background inhibition amount;and using the background inhibition amount to perform appropriate function mapping to obtain the image after background inhibition. The sea surface object image background inhibition method uses the depth study method to obtain the background inhibition amount of each pixel in the image by using the depth study according to the difference between the object and the background in the sea surface object image, and verifies through experiments that the sea surface object image background inhibition method has dramatic inhibition effect on the background of the sea surface target image.

Description

technical field [0001] The invention belongs to the technical field of image processing, and more specifically relates to a method for suppressing the background of a sea target image based on a convolutional neural network. Background technique [0002] Automatic target detection is an important part in the development of intelligent weapon systems. Infrared technology is widely used in self-seeking weapon systems because of its high sensitivity and frame rate, good concealment, and no time limit for use. Generally speaking, the angular resolution of infrared detectors is limited. When the target is far away, the detector receives low target radiation energy and receives radiation from other objects in the field of view at the same time, so most of the image after imaging is Complex background clutter with unstable spatial distribution (such as cloud background, ground background, sea-sky background, etc.), the target not only has a low signal-to-noise ratio, but also has ...

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Problems solved by technology

[0005] The present invention provides a sea surface target image background suppression method based on convolutional neural network, the purpose is to solve the

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