Digital image enhancement method based on optic nerve network

Abstract

The invention provides a digital image enhancement method based on an optic nerve network. The method comprises the following steps: S1, acquiring the image intensity of an image to be processed and compressing the image intensity within the dynamic range to obtain a compressed image; S2, extracting the contrast ratio of the image to be processed; and S3, modulating and uniting processing the compressed image according to the contrast ratio so as to obtain an enhanced image. The S1 and S2 are in no particular order. The digital image enhancement method achieves the purpose of completing image enhancement through combination of a lateral inhibition nerve network and a Weber code for describing the response of retina cone cells, and solves the problems of both color permanence and dynamic range compression mentioned in the prior art.

Description

technical field [0001] The invention relates to the field of image processing, in particular to a digital image enhancement method based on a visual neural network. Background technique [0002] Affected by the development of digital imaging equipment technology, there is a common and often serious gap between the output images of artificial imaging equipment and the real perception of physiological visual system. This problem is mainly caused by the following two limitations: 1. Changes in the spectral components of external light lead to color distortion in the image output by the imaging device, which is the so-called color constancy (color fidelity) problem. 2. Due to the limited dynamic output range of imaging equipment, the output image often loses details and color information in darker areas of the scene, which is the so-called dynamic range compression problem. [0003] The color constancy problem generally refers to the phenomenon that the output image of the imag...

AI Technical Summary

Problems solved by technology

[0002] Affected by the development of digital imaging equipment technology, there is a common and often serious gap between the output images of artificial imaging equipment and the real perception of physiological visual system

This problem is mainly caused by the following two limitations: 1. Changes in the spectral components of external light cause color distortion in the image output by the imaging device, which is the so-called color constancy (color fidelity) problem

2. Due to the limited dynamic output range of imaging equipment, the output image often loses details and color information in darker areas of the scene, which is the so-called dynamic range compression problem.

For digital imaging equipment, spectral offset is generally compensated by selecting the white balance mode, but none of the spectral correction methods used has the ability to compress the dynamic range. often can not be displayed at the same time

[0004] The problem of dynamic range compression is reflected in the mismatch between the huge difference in light intensity in the scene (often exceeding 10000:1) and the commonly used limited digital image output range (usually 8bit quantization, maximum 256)

This mismatch causes the details of the output image to be far weaker than the human visual perception

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