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Bionic image restoration method based on human visual characteristics

A technology of human visual characteristics and images, applied in the field of bionic image restoration that simulates the human visual system, can solve problems such as difficulty in finding the optimal network, inability to completely retain the original image, loss of smoothness and other characteristics of the observed image, and achieve restoration The effect of regional brightness contrast and brightness gradient information, strong image generalization ability, and good restoration effect

Inactive Publication Date: 2010-10-06
INST OF SEMICONDUCTORS - CHINESE ACAD OF SCI
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Problems solved by technology

But it has two inherent problems: 1) ill-conditioned problem, that is, a small change in the observed data may lead to a large change in the solution; 2) the problem of non-uniqueness of the solution, which is caused by incomplete information
However, these methods are difficult to find the optimal network, and may lose the smoothness and other characteristics of the observed image during the image restoration process, resulting in the inability to completely retain the information of the original image

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  • Bionic image restoration method based on human visual characteristics

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Embodiment Construction

[0027] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be described in further detail below in conjunction with specific embodiments and with reference to the accompanying drawings.

[0028] In order to quantitatively describe the input-output characteristics of the retinal ganglion cell receptive field, the present invention adopts a double Gaussian difference model (DOG model) to describe the traditional receptive field of the ganglion cell with concentric overlapping circular areas of different sizes. central and peripheral areas. However, studies have shown that there is a large-scale disinhibition area in the traditional receptive field. Based on the DOG model, a three-Gaussian model is proposed, and a third Gaussian kernel is added to represent a large-scale disinhibition area.

[0029] Biological studies have shown that the subjective brightness of the human eye is a logarithmic function of the ...

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Abstract

The invention relates to the technical field of image processing, and discloses a bionic image restoration method based on human visual characteristics, which comprises the following steps that: step 1: the brightness of an image is extracted; step 2: the neighborhood average brightness of a current point is calculated by gaussian filtration; step 3: the local linear relationship with actual light intensity logarithm is felt by the subjective brightness of human eyes, and the local contrast of the image is adjusted; and step 4: the brightness image with the adjusted local contrast is compared with the brightness of an original image to linearly adjust the color information of the image and realize the linear restoration of the image color. Experiments show that the method can effectively restore vague images, and particularly to image boundary regions, not only can enhance the border contrast but also can effectively improve the regional brightness contrast and the brightness gradient information.

Description

technical field [0001] The invention relates to the technical field of image processing, in particular to a bionic image restoration method that simulates the human visual system. Background technique [0002] Image restoration is an important part of image processing technology. It is not only widely used in scientific research and engineering practice in many fields such as astronomy, satellite remote sensing, medical imaging, industrial vision, military public security, etc., but also widely used in video restoration. , historical photo and film restoration, video and multimedia image restoration, and scanned document processing. A fundamental problem in image restoration is deblurring. The essence of image blur is that the image is subjected to averaging or integral operations. From the analysis of the frequency domain, the essence of image blur is that its high-frequency components are attenuated. Therefore, for example, differential operation or high-frequency weight...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T5/00
Inventor 金小贤李卫军陈旭
Owner INST OF SEMICONDUCTORS - CHINESE ACAD OF SCI
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