Non-reference image quality evaluation method based on wavelet-transformation multi-resolution prediction

Abstract

The invention discloses a non-reference image quality evaluation method based on wavelet-transformation multi-resolution prediction. The method comprises the following steps: (1) selecting an ideal image and calculating average energy of each scale and each direction after the wavelet transformation; (2) using an approximate linear relation between scale energy characteristics to establish a prediction model; (3) according to the prediction model, using high-scale sub-band average energy of a distorted image to predict low-scale sub-band average energy of an ideal image; (4) properly adjusting the predicted average energy of the serious distortion image; (5) compensating the energy of the noise distortion image; (6) compensating the energy of the JPEG distortion type image; (7) combining a human visual system characteristic to construct a non-reference image quality evaluation scale. According to the invention, subjectively scored training is not needed. The method is highly consistent with the subjective evaluation. The method is suitable for a plurality of distortion types and can be used to detect effectiveness of an image video processing method.

Description

technical field [0001] The invention relates to a non-reference image quality evaluation method based on wavelet transform multi-resolution prediction, which belongs to the technical field of image processing. Background technique [0002] Many aspects of image processing technology, such as compression, transmission, enhancement, storage, watermarking, etc., all require image quality evaluation, so the research on image quality evaluation methods is very valuable. There are two categories of methods for evaluating image quality: subjective and objective. In most cases, people are the ultimate recipients of image visual information, so using subjective experiments to evaluate image quality is the most accurate and effective method. However, in practice, the subjective method requires a large amount of experimental data, and is not easy to be embedded in the automatic system. The current research focuses on the objective image quality evaluation method. This method strives t...

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Problems solved by technology

The author of the paper gives the experimental results of this method for JPEG2000 compression, JPEG compression, white noise, Gaussian blur and Fastfading five types of distortion, compared with other evaluation methods that can only be applied to one or two types of distortion. Improvement, but the effect of this method is very poor on JPEG and white noise distortion. In fact, it can only be regarded as applicable to three types of distortion (JPEG2000 compression, Gaussian blur and Fastfading). For this purpose, better and more reliable no-reference image quality is developed. evaluation method becomes more valuable

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