A Color Image Deblurring Method Based on Blind Deconvolution

Abstract

The invention discloses a method for deblurring a color image based on blind deconvolution, which is characterized in that it comprises the following steps: reading in the original color blurred image I; mask MASK‑I; using maximum value suppression to mask MASK‑I B is refined; the mask MASK-B and the original color blurred image I are divided into blocks; the pixels in each block are arranged in the form of column vectors; the pixel values ​​​​of each column vector are added and summed; an effective column vector is selected Save; cluster the column vector; convert the new column vector into an image block; convert the new image block into a quasi-clear image X1; take the mask MASK-X1 for the image X1; perform Fourier deconvolution to obtain the blur kernel k1 ; Obtain the re-clear image of the three channels of RGB, and perform 4 iterations to obtain the final color and clear image. This method has good image deblurring effect, fast deblurring speed, simple method and easy implementation.

Description

technical field [0001] The present invention relates to the field of image processing, in particular to a method for deblurring color images based on blind deconvolution Background technique [0002] Image deblurring is to take the existing blurred image obtained by people, and use a specific method to remove the blur in the image, so as to obtain the ideal clear image. In recent years, as people have higher and higher requirements for image clarity, deblurring methods are emerging, and the application fields involved are becoming more and more extensive. It will blur the image, so it is of great significance to deblur the image in daily production and life. To achieve a better processing effect, blurring caused by different reasons often requires different processing methods. Divided according to the blurred area, it can be divided into: global blur and local blur. The global blur is mainly caused by the motion of the shooting device, while the local blur is caused by the...

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Problems solved by technology

(2) The reason for the global blur is that the hand-held shooting device shoots with a relatively long exposure time, and often encounters blurring during the shooting process.

The L-R algorithm needs to consider the prior information of the object and does not need the noise information of the blurred image. It is suitable for linear and nonlinear imaging models. The solution is unique, but it needs to increase the number of iterations and limit the deviation threshold to achieve better results. Therefore, there is a certain limitations; the restoration effect of the constrained least squares algorithm is better than that of the Wiener filtering algorithm, but the derivation assumption of the constrained least squares algorithm is that the random field is uniform and the spectral density is known, so it is not suitable for wide application; blind The deconvolution algorithm can restore the image and the point spread function (fuzzy kernel) at the same time, and can still restore the blurred image without prior knowledge of the distortion, so it has good practicability, but which also produces a ringing effect

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