Method of measuring main attributes of natural image

Abstract

The invention discloses a method of measuring main attributes of a natural image. The method is characterized by comprising the following steps: 1, the original image is processed according to the following methods and test images are obtained, wherein the methods are: 1, two times of JND (Just Noticeable Difference) amount of the white level of the original image are changed; 2, two times of JND amount of the black level of the original image are changed; 3, two times of JND amount of the color saturation of the original image are changed; and 4, two times of JND amount of the contour rendering of the original image are changed; 2, with the original image as a reference image, differences between any two groups of the above four groups of test images and the reference image are compared respectively, and the group of test images which has the largest difference with the reference image is found out; 3, different image contents and tested images are replaced, and the first step and the second step are repeated; and 4, a statistical model is adopted, a Z value corresponding to a different image attribute change amount is solved respectively, and significance statistical analysis is then carried out.

Description

Technical field [0001] The invention relates to a method for measuring the main attributes of an image, in particular to a method for measuring the main attributes of a natural image. Background technique [0002] In recent years, with the rapid increase in the number and diversity of various display technologies, people's requirements for display quality have increased day by day. New technologies and new applications may change the observer's evaluation of the display image quality. To this end, Engeldrum introduced the "image quality loop" model, which links the image display quality that consumers care about with the technical parameters of the display system through some intermediate steps. Consumers’ subjective perception of image quality is the weighted sum of the observed image quality attributes. These image quality attributes include sharpness, color richness, brightness, image uniformity and other characteristics that are unconsciously evaluated by the observer. The...

AI Technical Summary

Problems solved by technology

The problem faced by this method is that it does not consider the contrast, which is an important factor affecting image quality, nor does it consider the relationship between JNDs of different image attributes in horizontal contrast.

Images