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Excited response-based no-reference image quality evaluation method

A stimulus-response and quality evaluation technology, applied in the field of image processing, can solve problems such as insufficient image quality performance, insufficient understanding of statistical characteristics, etc.

Active Publication Date: 2018-06-15
ZHEJIANG UNIV
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Problems solved by technology

[0005] The purpose of the present invention is to propose an excitation-response-based No-reference image quality assessment method

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Embodiment Construction

[0049] The method of the present invention will be further described below in conjunction with the accompanying drawings.

[0050] Such as figure 1 As shown, a no-reference image quality evaluation method based on stimulus response, the specific implementation steps are as follows:

[0051] Step (1). The test image I in the input database (such as known databases such as LIVE, CSIQ, TID2008 and TID2013) under the Matlab environment D ;

[0052] Step (2). Construct the excitation signal R x , such as the following excitation signal:

[0053]

[0054] Step (3). Utilize the stimulus set up in step (2) to correspond to the distorted image I input in step (1) D Carry out convolution calculation to get the excitation corresponding signal I R :

[0055]

[0056] Among them, i represents the position of the pixel in the image, Represents a convolution operation.

[0057] Step (4). The stimulus response signal I R and distorted image I D To convert from RGB space to YI...

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Abstract

The invention discloses an excited response-based no-reference image quality evaluation method. The method comprises the following steps of: 1, constructing an excitation signal, and applying the excitation signal on a to-be-evaluated image to obtain an excitation response signal; converting the to-be-evaluated image and the excitation response signal from an RGB space to a YIQ space; constructinga group of two-dimensional edge detection operators, and carrying out convolution processing on components, on a Y channel of the YIQ space, of the to-be-evaluated image and the excitation response signal, so as to obtain feature information of the components, on the Y channel, an I channel and a Q channel of the YIQ space, of the to-be-evaluated image and the excitation response signal; and taking the feature information as input, and carrying out quality evaluation on image quality mapping of a to-be-tested image by utilizing a machine learning method, so as to obtain an objective quality evaluation value of the to-be-evaluated image. The method is capable of effectively extracting feature information of images, and is high in operation speed and relatively low calculation complexity; on the basis of the method, the objective image quality evaluation values are relatively consistent with subjective evaluation, so that image quality can be well evaluated.

Description

technical field [0001] The invention belongs to the technical field of image processing, in particular to a stimulus-response-based no-reference image quality evaluation method. Background technique [0002] Most of the information humans get comes from our visual system, which means we get most of the information we need from images. It can be seen that images play a very important role in our daily life, but image distortion is often introduced during the process of image acquisition, storage, compression, transmission and reconstruction, resulting in loss of image quality. Image quality evaluation uses a certain evaluation standard to measure the loss of image quality, which is an important index to measure and optimize the performance of image and video processing systems, and has important application value. [0003] Subjective evaluation and objective evaluation are two main methods of image quality evaluation. Subjective quality evaluation is to use the observer to ...

Claims

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Application Information

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IPC IPC(8): G06T7/00
CPCG06T7/0002G06T2207/10024G06T2207/20081G06T2207/30168
Inventor 丁勇谢欣商小宝周一博孙光明罗述杰
Owner ZHEJIANG UNIV
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