Night vision image salient contour extracting method based on non-classical receptive field composite modulation

Abstract

The invention discloses a night vision image salient contour extracting method based on non-classical receptive field composite modulation. A multi-scale iterative noticing method is constructed according to a non-classical receptive field composite modulation model, the scale factor of non-classical receptive field composite modulation is dynamically changed in the iterative process, and a composite modulation result of an input night vision image is calculated. In each step of the iterative process, for each pixel of the input image, a multi-dimensional feature contrast MFC weighted inhibition model is adopted to calculate an inhibition result of each pixel first, then, a facilitation result of each pixel is calculated based on a grouping excited voting GEV facilitation model, and finally, non-classical receptive field composite modulation output is obtained. By adopting the method of the invention, the problem of noise and texture suppression in low-light and infrared images and the problem of contour discontinuity caused by imaging characteristics, environment inhibition and noise interference are solved.

Description

technical field [0001] The invention belongs to the field of night vision image understanding, in particular to a method for extracting salient contours of night vision images in complex scenes based on vision modeling. Background technique [0002] Contour extraction plays an important role in the understanding and analysis of night vision images (low light, infrared images). At present, most of the applications of night vision target detection and recognition are for outdoor scenes, so night vision images contain a large number of natural textures (such as trees and grass). The result of the traditional edge detection operator retains a large number of non-contour edge components (canny operator). How to remove these local uninteresting edges generated by texture places and maintain the integrity of the contour is aimed at low-light and infrared image features. The main problems faced by night vision image contour detection. [0003] Many solutions have been proposed for...

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Problems solved by technology

[0005] In order to solve the problem of inaccurate night vision image environment suppression, the present invention introduces multi-feature analysis on the basis of the nCRF suppression model, and weights the suppression effect according to the multi-dimensional feature difference contrast of night vision images, so as to improve the accuracy of environment suppression and achieve a more thorough background texture and noise suppression; in order to solve the problem of contour fracture, the present invention introduces a facilitation mechanism with contour grouping function on the basis of the nCRF suppression model, so that weak contours can be enhanced and inter-crack contours can be connected, so that night vision can be maintained Integrity of image contours to improve object detection performance

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