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Color distorted image estimation method based on hypercomplex number color rotation

A color distortion and color image technology, which is applied in the field of color distortion image evaluation method, can solve problems such as ignoring image color correlation, inaccuracy, and one-sided evaluation results

Inactive Publication Date: 2008-08-20
FUDAN UNIV
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Problems solved by technology

At present, the quality evaluation of color distorted images is to extract the brightness information of the color image, and then process it according to the grayscale image evaluation method; or in order to obtain better results, each component of the color image can be processed separately, and then the obtained The results are added and averaged, but this processing method also ignores the color correlation of the image, and the evaluation results are often one-sided and inaccurate

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  • Color distorted image estimation method based on hypercomplex number color rotation
  • Color distorted image estimation method based on hypercomplex number color rotation
  • Color distorted image estimation method based on hypercomplex number color rotation

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Embodiment Construction

[0052] The specific implementation manner of the color distortion evaluation of the color image carried out by the present invention is as follows:

[0053] 1. In order to evaluate the color image quality, we first perform hypercomplex modeling on the color image, that is, express the RGB model of each pixel in the original color image f and the color distorted image g to be evaluated as a pure supercomplex form: f (x, y) = f R (x,y)i+f G (x,y)j+f B (x,y)k and g(x,y)=g R (x,y)i+g G (x,y)j+g B (x,y)k. Among them, (x, y) is the coordinate of the pixel in the color image, that is, the position of the row and column of the matrix where the pixel is located.

[0054] 2. Decompose the original color image f and the distorted image g into 8×8 small blocks, and obtain the “block color” of the unit small block from the average value of red, green, and blue of all pixels in each 8×8 unit small block vector":

[0055] f BLOCK = ...

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Abstract

The invention belongs to the image signal processing technique field. Particularly the invention relates to a a color fault image evaluating method based on a supercomplex heterochromia conversion. Currently quality evaluation for the color fault image or extracting luminance information of color image, or separately processing each component of the color image and then averaging, such all neglect color association of the image and usually cannot gain the exact color fault image evaluation. The invention partitionings the whole image, processes a specifically supercomplex rotating for fault image piece so as to gain the fault image and heterochromia among the original images, and averages the heterochromia of all pieces to process the color fault evaluation of the whole image. A experiment proves that, for the color fault image, the invention can gain an evaluate result corresponding to subjective visual effects, and the invention also has the advantages of simple operating, small calculated amount, superior to the method of extracting the luminance information of the color image to process to evaluate, and also having a better effect than the method of separately processing each component of the color image and then averaging.

Description

technical field [0001] The invention belongs to the technical field of image signal processing, and in particular relates to a color distortion image evaluation method based on super-complex color rotation. Background technique [0002] Image quality assessment is one of the basic technologies of image information engineering. In image communication engineering, the optical image of the subject is transmitted to the receiving end, and an acceptable image is reproduced, which requires photoelectric conversion, transmission, processing, recording and other transformation processes. The advantages and disadvantages of all these technologies will be collected to the evaluation of image quality. At present, the evaluation of image quality can be divided into two categories: subjective evaluation and objective evaluation. [1] . Subjective evaluation method The evaluation of visual quality adopts the method of subjective scoring, and a test protocol must be followed when perform...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H04N1/60H04N17/00G06T7/00
Inventor 江淑红张建秋胡波
Owner FUDAN UNIV
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