SAR image denoising method based on contour wave domain block hidden Markov model

A Hidden Markov and Contour Wave technology, applied in the field of image processing, can solve the problems of lack of spatial adaptability and blurred edges of SAR images, and achieve the effect of overcoming spatial adaptability.

Active Publication Date: 2010-02-03
XIDIAN UNIV
View PDF0 Cites 20 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the application of the CD-CHMM model to SAR image de

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • SAR image denoising method based on contour wave domain block hidden Markov model
  • SAR image denoising method based on contour wave domain block hidden Markov model
  • SAR image denoising method based on contour wave domain block hidden Markov model

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0036] refer to figure 1 , the specific implementation steps of the present invention are as follows:

[0037] Step 1: Perform logarithmic transformation on the input SAR image, and convert the multiplicative noise into additive Gaussian white noise for processing: log y=log z+log x, where y represents the input SAR image, z represents the noise image, and x represents no Noise image; Contourlet decomposition is performed on the image after logarithmic transformation, in which the direction of the directional filter is 4, 4, 4, and the Contourlet transformation coefficient is obtained to obtain the high-frequency Contourlet coefficient.

[0038] Step 2: Establish an improved BlockHMM model in the Contourlet domain for the obtained high-frequency Contourlet coefficients, such as figure 2 shown.

[0039] The specific implementation is as follows:

[0040] (2a) The parent node between scales, sibling nodes between directions and neighborhood nodes within scale jointly determi...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention discloses a SAR image denoising method based on a contour wave domain block hidden Markov model, belonging to the field of image processing, mainly solving the problem of space adaptability shortage, serious detail information loss and fuzzy edge of current method, and comprising the following steps: (1) carrying out logarithmic transformation and Contourlet decomposition; (2) carrying out Block HMM modeling and training on a Contourlet coefficient; (3) correcting the Contourlet coefficient by estimation parameters; (4) carrying out Contourlet inverse transformation and antilogarithm transformation to the corrected Contourlet coefficient in order to obtain a one-time denoising image; (5) denoising a difference value image to obtain a second-time denoising image; and (6) fusing the one-time denoising image and the second-time denoising image and rotating and translating the fused image to obtain and output a final denoising image. The SAR image denoising method improves the space adaptability, reduces the calculation complexity and increases the edge resolution of the denoised image.

Description

technical field [0001] The invention belongs to the technical field of image processing, and in particular relates to a method for suppressing SAR image speckle noise, which can be used for denoising processing of SAR images, medical images and natural images. Background technique [0002] Synthetic aperture radar (SAR) has all-weather and all-weather earth observation capabilities, and can also obtain information through the surface and vegetation, playing an increasingly important role in military, remote sensing and other fields. The existence of speckle noise in SAR images seriously affects the accuracy of subsequent automatic interpretation and scene understanding tasks. Therefore, the removal of speckle noise is very important to the subsequent processing of SAR images. [0003] Speckle noise removal usually includes spatial filtering and transform domain methods. Spatial filtering such as Gamma-MAP to denoise SAR images can effectively reduce the influence of noise ...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
IPC IPC(8): G06T5/00G06T5/50G01S13/90
Inventor 焦李成侯彪田福苓王爽张向荣马文萍
Owner XIDIAN UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap