Frequency domain saliency target detection method based on Gabor wavelets

Abstract

The invention relates to a frequency domain saliency target detection method based on Gabor wavelets. The method includes the steps: S1, switching inputted color images into gray images and building a directional feature map; S2, building two color feature maps according to sensitivity of human eyes on different colors of the inputted color images; S3, building a gray feature map for the inputted color images; S4, building a polynomial matrix by the aid of the four feature maps; S5, performing Fourier transformation for the polynomial matrix comprising the four feature maps to obtain a frequency domain polynomial matrix and extracting a magnitude spectrum matrix; S6, performing Gaussian low-pass filter for the magnitude spectrum matrix by a plurality of scales and performing polynomial inverse Fourier transformation for a group of magnitude spectra to obtain a plurality of time domain polynomial matrixes; and S7, dividing the time domain polynomial matrixes into different time domain polynomials according to different scale factors, building a histogram for each time domain polynomial, calculating a one-dimensional entropy function and extracting a time domain saliency map corresponding to the minimum information entropy as a final detection result.

Description

technical field [0001] The present invention relates to a method of using Gabor wavelet and Fourier transform to detect salient targets without using any prior knowledge of target images, and is a technique for detecting images using a visual psychology model, which is used for image processing, image Compression, computer vision, and object detection tracking localization. Background technique [0002] The visual attention model is a model that uses a computer to simulate the human visual attention system. It extracts the attention-grabbing focus that the human eye can observe in an image. Compared with the computer, it is the salience of the image. area. The human visual system requires both the ability to process a large amount of input information and the quasi-real-time response ability. Visual psychology studies have shown that when analyzing complex input scenes, the human visual system adopts a serial computing strategy, that is, using the selective attention mecha...

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Problems solved by technology

Although this algorithm can obtain the position and outline of the target, it cannot identify th

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