Blurring kernel multi-scale iteration estimation method using directional derivative of image local structure

A technology of local structure and directional derivatives, applied in image data processing, image enhancement, calculation, etc., can solve the problem of unsatisfactory image restoration effect, achieve the effect of reducing ringing effect, reducing computational complexity, and wide application prospects

Active Publication Date: 2013-05-08
NANJING UNIV OF SCI & TECH
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Problems solved by technology

This method uses the edge information of the blurred image to perform shock filtering on the blurred edge, and then alternately iteratively estimates the blur kernel and restores the image. This method can quickly and better estimate the blur kernel, but for images with more textures, this method is not ideal for image recovery

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  • Blurring kernel multi-scale iteration estimation method using directional derivative of image local structure
  • Blurring kernel multi-scale iteration estimation method using directional derivative of image local structure
  • Blurring kernel multi-scale iteration estimation method using directional derivative of image local structure

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Embodiment Construction

[0039] The present invention uses the fuzzy kernel multi-scale iterative estimation method of the directional derivative of the image local structure. Based on the image decomposition and the local structure directional derivative, the directional gradient vector field is solved iteratively through multi-scale, and the fuzzy kernel is predicted and the image is restored in an alternate manner. To achieve the purpose of fuzzy kernel estimation. The present invention uses image decomposition to decompose the blind restoration image in the iterative process into cartoon part and texture part, obtains the directional gradient field of the cartoon part after impact filtering, uses the obtained gradient field to alternately finely predict the blur kernel and the restored image, and the iteration terminates Then get the final fuzzy core.

[0040] Such as figure 1 As shown, the present invention uses the fuzzy kernel multi-scale iterative estimation method of the directional derivative ...

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Abstract

The invention discloses a blurring kernel multi-scale iteration estimation method using a directional derivative of an image local structure. The blurring kernel multi-scale iteration estimation method comprises inter-scale updating, intra-scale iteration estimation and inter-scale iteration termination judgment. A blurring kernel and a recovering image are estimated from coarse scale iteration to fine scale iteration. The intra-scale iteration estimation comprises the following steps: calculating an enhanced type direction gradient filed of a current scale; estimating a blurring kernel of the current scale rapidly; calculating a directional derivative approximate spectrum of a current image; and recovering an image of the current scale. Gradient information of image jumping edges is utilized, with a quick Fourier transform technology based on, the blurring kernel is quickly estimated in a small time complexity, and the blurring kernel multi-scale iteration estimation method can be used for conducting blind deblurring on various actual blurring images.

Description

Technical field [0001] The invention belongs to the field of computer digital image processing, in particular to a fuzzy kernel multi-scale iterative estimation method using the directional derivative of the image local structure. Background technique [0002] Camera shake is a problem that has always plagued photographers. An unstable camera can cause blurry photos. In particular, the current popular small high-resolution digital cameras, due to their light body weight, make them difficult to hold stably during use. Many photos capture short precious moments that cannot be reproduced. If the camera shakes at this time, these precious moments will be completely lost. Therefore, it is particularly important to work on finding ways to remove camera shake from a single photo. [0003] Image deblurring can be divided into two main categories: non-blind deblurring of image and blind deblurring of image. Image non-blind deblurring refers to the process of obtaining the original clear ...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T5/00
Inventor 王凯肖亮韦志辉
Owner NANJING UNIV OF SCI & TECH
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