High-dynamic image display method based on biological vision mechanism

Abstract

The invention discloses a high-dynamic image display method based on a biological vision mechanism, and is applied to the technology of image display. The method introduces a horizontal cell dynamic reception field and a bipolar cell Gaussian difference reception field to high-dynamic image brightness range compression, thereby effectively improving the light and shadow region details while maintaining the color and global contrast. Moreover, the method achieves the adaptive adjustment of the size of the horizontal cell dynamic reception field based on the local brightness, and is more suitable for the physiological characteristics. In addition, the method can achieve the consistent capability of a vision system in quickly obtaining the stable perception in different natural light environments.

Description

technical field [0001] The invention belongs to the technical field of image display, in particular to a high dynamic image enhancement technology based on retinal vision mechanism. Background technique [0002] The dynamic range of brightness in natural scenes in the real world is extremely large, and the contrast between light and dark is as high as 10 14 . The high dynamic range image collected by the high dynamic range image acquisition technology can completely contain the real light intensity information of each point in the original scene. However, the dynamic range of common display media, such as monitors, generally does not exceed 10 2 . The limited dynamic range of common display media has seriously affected the use of high dynamic range images with complete scene information in security monitoring, telemedicine, film and television animation and other fields. Therefore, how to display the bright and dark areas, texture details and color features of the high d...

AI Technical Summary

Problems solved by technology

The global processing method uses a unified operator to operate on the entire image. The advantage is that the calculation is simple and it is not easy to introduce artifacts. The disadvantage is that the overall effect is not satisfactory, and it is often impossible to display the brightest and darkest areas at the same time.

The local processing method distinguishes the areas of different brightness of the image, which solves the problems faced by the global processing method, but it faces a series of problems such as brightness inversion, color distortion, and scene contrast loss.

Among them, the most common problem in the display results of different local processing methods is that there will always be dark or bright halos at the border of the light and dark border

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