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Method for super resolution of single-frame images

A technology of super-resolution and super-resolution technology, which is applied in the field of image processing to achieve the effects of improving clarity, suppressing noise, and suppressing ringing artifacts

Inactive Publication Date: 2009-09-23
李金宗
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  • Application Information

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Problems solved by technology

[0004] Currently, various super-resolution methods are usually very sensitive to their assumed models of data and noise, thus limiting the application

Method used

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  • Method for super resolution of single-frame images

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Experimental program
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Embodiment 1

[0067] Single-frame image super-resolution method, first analyze the image, and decide whether to perform image restoration processing to eliminate noise, blur and cloud according to the analysis results; Domain anti-aliasing super-resolution method for processing; then through Fourier transform, frequency domain anti-aliasing algorithm and Fourier inverse transform, enrich the texture and details of the image, improve the clarity, contrast and resolution of the image, and suppress ringing illusion.

[0068] The frequency aliasing depth of:

[0069]

[0070] where the spectral width is 2π; C 11 It is the frequency aliasing depth (FAD) parameter, which reflects the degree of aliasing at the high end of the spectrum. C 11 The extraction process includes: performing Fourier transform on the under-sampled low-resolution image; performing global polynomial least squares fitting on the spectrum of the low-resolution image; Carry out quadratic truncation fitting; perform spect...

Embodiment 2

[0133] Most of the actual images contain more or less noise. For this reason, firstly, the above-mentioned iterative blind deconvolution algorithm based on FT is used to perform the simulation experiment of the fuzzy restoration operation on multiple groups of noisy blurred images, and the effect of deblurring and the number of iterations are studied. N relationship. In the experiment, first use the defocus blur matrix whose size is 3×3 to convolve the original image, and add N(0, 5) Gaussian noise to obtain a noisy blurred image; for the noisy blurred image The image is defuzzified, and the number of iterations N is changed from 1 to 6 to obtain the defuzzified image. Then, calculate the peak signal-to-noise ratio (PSNR) for the blurred image and the image after deblurring, and then obtain the relationship curve between the PSNR increase value and the number of iterations N of the three sets of experimental results of the blind deconvolution algorithm, and then get the number...

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Abstract

The invention relates to a method for super resolution of single-frame images. In the imaging process, an imaging system fuzzes up and deforms the original object images; and at the same time, an analog-digital (A / D) conversion process CCD therein is lack of sampling, frequency aliasing is caused, high-frequency information is lost, and frequency spectrum aberrations appear at a frequency aliasing section, so not only the frequency spectrum of a real image scenery becomes narrow, but also the structure of a high frequency section is changed due to resolution losses caused by design limitations of an image device. The method for the super resolution of the single-frame images comprises the following steps of: firstly, analyzing images, and determining whether a single-frame frequency domain de-aliasing super resolution method is to be adopted to perform processing through frequency aliasing parameters; and secondly, enriching the texture and the detail of the images through a Fourier transform, a frequency domain de-aliasing algorithm and an inverse Fourier transform so as to improve the definition, the contrast and the resolution of the images and inhibit ringing pseudo images. The method is applied to the fields of satellite remote sensing image processing, medical image and earthquake image analysis and the like.

Description

Technical field: [0001] The invention relates to a method for analyzing and processing an image so as to significantly improve the resolution, clarity and contrast of the image, which belongs to the category of image processing. Background technique: [0002] During the imaging process of the imaging system, the original object image is blurred and deformed due to atmospheric turbulence and interference, visibility effects, optical effects, and integral effects in the photoelectric signal conversion process; at the same time, due to the modulus (A / D) Under-sampling in the transformation process will cause frequency aliasing, loss of high-frequency information, and spectral distortion in the frequency aliasing section. Therefore, not only the spectrum of the real image scene is narrowed, but also the frequency spectrum of the high-frequency band is changed. Structure, which is due to the loss of resolution caused by the design limitations of imaging equipment, is also the ma...

Claims

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Application Information

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IPC IPC(8): G06T3/40G06T5/00
Inventor 李金宗李冬冬马冬冬杨学峰
Owner 李金宗
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