Unlock instant, AI-driven research and patent intelligence for your innovation.
A sparse regularization feature enhancement method for SAR image interpretation
What is Al technical title?
Al technical title is built by PatSnap Al team. It summarizes the technical point description of the patent document.
A feature enhancement and image feature technology, applied in image enhancement, image analysis, image data processing, etc.
Active Publication Date: 2019-03-12
AIR FORCE UNIV PLA
View PDF3 Cites 4 Cited by
Summary
Abstract
Description
Claims
Application Information
AI Technical Summary
This helps you quickly interpret patents by identifying the three key elements:
Problems solved by technology
Method used
Benefits of technology
Problems solved by technology
From the existing literature, there is no method for regularized feature enhancement for the purpose of interpretation.
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
Click on the blue label to locate the original text in one second.
Reading with bidirectional positioning of images and text.
Smart Image
Examples
Experimental program
Comparison scheme
Effect test
Embodiment 1
[0071] Embodiment 1: SAR image sparse regularization feature enhancement method for the purpose of interpreting, comprising the following steps:
[0072] Establish a SAR image feature enhancement model based on a sparse regularization framework;
[0073] Based on L 1 / 2 The norm ITA algorithm solves the SAR image feature enhancement model in the first step;
[0074] Output SAR image feature enhancement results.
Embodiment 2
[0075] Embodiment 2: Describe in detail below, establish the SAR image feature enhancement model based on the sparse regularization framework:
[0076] The SAR image feature enhancement model based on the sparse regularization framework can be expressed as:
[0077] Y=X+N (1)
[0078] Among them, Y is the traditional SAR imaging result based on matched filtering, X is the feature enhancement result obtained by sparse regularization reconstruction, and N is a matrix with the same dimension as X, indicating that the enhancement result is different from the original image, which contains systemnoise , sidelobe to be removed, background clutter, etc. Using sparse regularization theory, X can be solved by formula (2):
[0079]
[0080] in Indicates the F-norm of the matrix, Indicates the q (0
Embodiment 3
[0082]Embodiment 3: Describe in detail below, adopt based on L 1 / 2 The norm ITA algorithm solves the above SAR image feature enhancement model based on the sparse regularization framework:
[0083] The iterative threshold algorithm is used to solve the SAR image feature enhancement model established above. Specifically, formula (2) can be solved by an iterative threshold algorithm formula (3):
[0084]
[0085] where n is the number of iterations and μ is the convergence parameter. Is the threshold operation in the ITA algorithm, consisting of a vector as follows:
[0086]
[0087] where N is the azimuth dimension of the matrix. In this vector The form of is determined by the norm q, when q=1 / 2, the article "L1 / 2Regularization: A Thresholding Representation Theory and a FastSolver" (IEEE Trans.Neural Networks Learning Sys,2012,23(7),1013–1028) Formula (5) is derived from:
[0088]
[0089] in:
[0090]
[0091] get X every time (n+1) After calculating the...
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
Login to View More
Abstract
The invention provides a SAR image sparse regularization feature enhancement method aiming at interpretation, which comprises the following steps: a SAR image feature enhancement model based on a sparse regularization framework is established; The SAR image feature enhancement model based on sparse regularization framework is solved by using the iterative threshold algorithm based on L1 / 2 norm, and the SAR image feature enhancement results are outputted. The regularization feature enhancement method of SAR image takes target detection of SAR image as the final goal, judges the feature enhancement changes of potential target region and background region through the designed rectangular window detector, and optimizes the regularization parameters adaptively. The final image enhancement results can effectively improve the target detection rate of the existing SAR target detection algorithm and reduce the false alarm rate.
Description
technical field [0001] The invention relates to a synthetic aperture radarimage processing technology, in particular to a SAR image sparse regularization feature enhancement method for the purpose of interpretation. Background technique [0002] Synthetic Aperture Radar (SAR) is a microwave imaging device with extremely high resolution. It uses pulse compression technology and synthetic aperture principle to realize imaging of ground scenes. It plays an important role in environmental monitoring, resource exploration, surveying and mapping, and battlefield reconnaissance. SAR image interpretation technology, that is, the technology of marking, identifying and understanding the regions of interest or targets in SAR images, has achieved rapid development in recent years. With the continuous improvement of SAR image resolution and the rapid development of computer technology, the automatic target detection and recognition of high-resolution SAR images by computer has become a...
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
Application Date:The date an application was filed.
Publication Date:The date a patent or application was officially published.
First Publication Date:The earliest publication date of a patent with the same application number.
Issue Date:Publication date of the patent grant document.
PCT Entry Date:The Entry date of PCT National Phase.
Estimated Expiry Date:The statutory expiry date of a patent right according to the Patent Law, and it is the longest term of protection that the patent right can achieve without the termination of the patent right due to other reasons(Term extension factor has been taken into account ).
Invalid Date:Actual expiry date is based on effective date or publication date of legal transaction data of invalid patent.