JND (Just Noticeable Difference) value measuring method and prediction method for dark field brightness of image

Abstract

The invention discloses a JND (Just Noticeable Difference) value measuring method for the dark field brightness of an image. The method comprises the following steps: switching an original image to an xyY space, performing linear compression on a component Y according to different compression coefficients respectively, and increasing the dark field brightness of the image to obtain a group of test images; conducting a visual perception experiment to find at least one test image for serving as a JND critical image; and calculating the difference values of practical display brightness corresponding to the gray value of each pixel of the original image and the JND critical image, wherein the average value of the difference values is the JND value of the dark field brightness of the original image. The invention further discloses a JND value prediction method for the dark field brightness of an image. The JND value prediction method is used for predicting the JND value of the dark field brightness of the original image. Through adoption of the JND value measuring method and detection method, display parameters can be evaluated and improved quantitatively. In particularly, human eye noticeable influences on the dark field brightness of the image in parameter design specific to dark field brightness and contrast are lowered, so that a basis is laid for the design and research of a display technology.

Description

technical field [0001] The invention relates to a method for measuring dark field brightness of an image, in particular to a method for measuring a JND (Just Noticeable Difference: just noticeable difference) value of the dark field brightness of an image. Background technique [0002] Display technology can not only realize accurate, intuitive, clear and fast information output, but also provide a friendly interface for man and machine to exchange information for the information age. Market research shows that display image quality is one of the most important determinants for end users to purchase electronic display devices. Therefore, the evaluation of information display quality is an important content in the field of display technology. Since all displayed information is observed by the observer through human eyes, people's judgments on image quality are different for different environments and uses. Therefore, the human factor must be considered in the evaluation of ...

AI Technical Summary

Problems solved by technology

Improving the contrast can be solved by increasing the brightness in the bright field and reducing the brightness in the dark field. However, it is very difficult to increase the brightness and increase the power consumption. The easiest way to improve the contrast is to reduce the brightness of the dark field.

However, the existing dark-field luminance JND measurement technology is difficult to apply to any natural image, for example, DICOM [Digital Imaging and Communications in Medicine (DICOM), Standard-PS 3.14-2003 [S], Part 14: Grayscale Standard Display Function, ( 2003), p21-27] standards released the human eye's perception threshold of brightness changes under different brightness conditions, but it was carried out under strict observation conditions, and the test chart of uniform color blocks was used instead of natural images

Xia Jun et al [Just-noticeable-difference of influential factors of subjective images quality, Xia Jun, Qin Shaoling, Liu Lu, Yin Hanchun, Journal of Southeast University (Natural Science Edition) , 36(5), 2006, p695-699] also did a preliminary study on the JND of dark field brightness. Only two natural images were selected, and the experimental method used was the paired comparison method, which can only give the dark field brightness Rough Interval Values ​​for JND

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