Image processing method

An image processing and image technology, which is applied in the field of image technology processing, can solve the problems of blurred image reconstruction effect, noise pollution of reconstruction results, and difficulty of reconstruction results from noise pollution, so as to achieve the goal of not being easily blurred or suffering from noise pollution Effect

Active Publication Date: 2016-04-06
CHENGDU UNIV OF INFORMATION TECH
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Problems solved by technology

[0011] The invention provides an image processing method, which solves the technical problems that the reconstruction effect of image details is easily blurred and the reconstruction result is easily polluted by noise in the existing single-frame image super-resolution reconstruction method based on the idea of ​​non-uniform interpolation, and realizes The image reconstruction effect is not easy to be blurred, and the reconstruction result is not easy to suffer from the technical effect of noise pollution

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Embodiment 1

[0052] Please refer to figure 1 , the specific implementation process of the single-frame image super-resolution reconstruction method proposed by the present invention is as follows:

[0053] [1] Input a low-resolution image containing noise;

[0054] [2] Use the classical kernel regression method to interpolate the input image to obtain an initial estimate and the value of the first derivative with

[0055] The kernel function used in classical kernel regression is: where h=1;

[0056] [3] For For each pixel m of , use its pixel neighborhood w i of all pixels within with Value, calculate the covariance matrix C of the pixel i , in the present invention, the neighborhood size is 7×7:

[0057] C i = Σ m i ∈ w m ...

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Abstract

The invention discloses an image processing method, and the method comprises the steps: firstly inputting an image L polluted by noises; secondly carrying out the interpolation of the image L, and obtaining the initial estimation of the image L and the first-order derivative of the image; thirdly constructing the covariance matrix of all pixels in the image through employing the first-order derivative calculated at step B; fourthly constructing an adaptive kernel function based on the covariance matrix; fifthly carrying out the adaptive sharpening of the adaptive kernel function; finally achieving the interpolation through employing a weight matrix after adaptive sharpening, and obtaining a final image. The method achieves a purpose that an image reconstruction image is not liable to be affected, and the reconstruction result is not liable to be polluted by noises. Moreover, the method effectively solves problems of image edge blur and noises.

Description

technical field [0001] The present invention relates to the field of image technology processing, in particular to a single-frame image super-resolution reconstruction method based on an adaptive sharpening strategy. Background technique [0002] With the popularity of image capture devices such as smart phones and digital cameras, digital images have become an important information medium for people to analyze and understand the natural environment. According to statistics, 80% of the information that humans can perceive comes from visual information with images as carriers. One of the important indicators to measure the quality of digital images is image resolution. The higher the resolution, the clearer the image and the richer the information it can provide. However, limited by the physical conditions of imaging equipment, the acquired digital images often have low resolution and contain noise. [0003] Single-frame image super-resolution reconstruction converts an inp...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T3/40
CPCG06T3/4053
Inventor 胡靖吴锡
Owner CHENGDU UNIV OF INFORMATION TECH
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