Switching non-local total variation based filtering method for image polluted by salt and pepper noise

A technology of salt and pepper noise and image filtering, applied in the field of image denoising, which can solve problems such as inability to effectively restore images

Active Publication Date: 2013-10-02
HUAZHONG UNIV OF SCI & TECH
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Problems solved by technology

Although the NLM method and the NLTV method can restore images polluted by Gaussian noise, they cannot effectively restore images polluted by impulse noise.

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  • Switching non-local total variation based filtering method for image polluted by salt and pepper noise
  • Switching non-local total variation based filtering method for image polluted by salt and pepper noise
  • Switching non-local total variation based filtering method for image polluted by salt and pepper noise

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Embodiment Construction

[0066] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention. In addition, the technical features involved in the various embodiments of the present invention described below can be combined with each other as long as they do not constitute a conflict with each other.

[0067] Such as figure 1 As shown, the salt and pepper noise pollution image filtering method based on switch non-local total variation of the present invention comprises the following steps:

[0068] The first step preprocesses the image contaminated by salt and pepper noise through a two-stage morphological detection operator to obtain the reference image and the noise flag, which specifically...

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Abstract

The invention discloses a switching non-local total variation based filtering method for an image polluted by salt and pepper noise, which comprises the following steps: performing pre-processing for the image polluted by salt and pepper noise through a two-stage morphological detector, so as to obtain a reference image and noise flag bit; based on the noise flag bit, filtering the reference image by utilizing an improved non-local total variation method, so as to obtain a denoised image. Due to the adoption of the method, noise distribution condition of the image can be effectively detected, with very lower omission ratio and false detection ratio. Besides, based on the reference image, the similarity between two images can be accurately calculated, the salt and pepper noise can be effectively suppressed while specific information including the image edge and texture can be well protected, and optimized peak value signal-to-noise ratio and structure similarity can be offered compared with a conventional filtering method for the salt and pepper noise.

Description

technical field [0001] The invention belongs to the field of image denoising, and more specifically relates to a switching non-local full variation filtering method for an image polluted by salt and pepper noise. Background technique [0002] In the process of image acquisition or transmission, due to electromagnetic or mechanical errors, the image will inevitably be polluted by impulse noise. Salt and pepper noise is a common impulsive noise, which will seriously affect the quality of the image and bring great difficulties to the subsequent image processing such as image segmentation and feature extraction. It is of great theoretical value and practical significance to study effective salt and pepper noise removal methods to effectively protect image details such as edges and textures while reducing image noise. [0003] For the salt and pepper noise in the image, the current mainstream noise reduction technology is a decision-based filtering method, that is, the noise det...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T5/00
Inventor 冯建滨张旭明朱玉坤钱烨吴意丁明跃尹周平王瑜辉
Owner HUAZHONG UNIV OF SCI & TECH
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