Significance target detection method fusing boundary priori and frequency domain information

Abstract

The invention discloses a saliency target detection method fusing boundary priori and frequency domain information. The method mainly comprises the steps of: grouping pixels through the similarity of features of the pixels, and replacing a large number of pixels with a small number of superpixels to express the feature information of a picture; assuming, by a boundary priori model, that the boundary of the image is a non-salient region and takes the non-salient region as priori knowledge; selecting lBP texture features to measure texture differences between the superpixels so as to represent boundary features of superpixel blocks; converting a non-boundary region of the boundary prior feature map to a frequency domain through Fourier transform, so that detection of a frequency domain saliency region is realized; fusing a boundary prior saliency map and a frequency domain feature saliency map; and carrying out image enhancement on a primary saliency map by adopting homomorphic filtering to obtain a final saliency map with a clear salient region. According to the method, boundary information and frequency domain information are combined, and a salient region with a more complete boundary can be detected for a salient target in a complex scene.

Description

technical field [0001] The invention belongs to the technical field of image processing, and in particular relates to a salient target detection method which fuses boundary prior and frequency domain information. Background technique [0002] Saliency detection is the use of image processing techniques and computer vision algorithms to locate the most "salient" areas in a picture. A salient area refers to an eye-catching area or a relatively important area in a picture, for example, the area that the human eye will first pay attention to when viewing a picture. data processing. Lock the area of ​​interest or target area in the visual scene, thereby reducing the amount of data processing and speeding up the speed of information processing, which is very attractive for various machine vision applications with limited computing resources and high real-time requirements , so target detection has received extensive attention from academia. [0003] In recent years, some high-p...

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Problems solved by technology

[0007] The HFT algorithm can suppress most of the background area, but the boundary of the foreground area is not clear, and the target cannot be well highlighted, which does not meet the needs of human visual experience.

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