Severity: Warning
Message: file_get_contents(https://...@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 176
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 1034
Function: getPubMedXML
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3152
Function: GetPubMedArticleOutput_2016
File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 316
Function: require_once
Image detail enhancement is critical to the performance of infrared imaging systems because the original images generally suffer from low contrast and a low signal-to-noise ratio. Although conventional decomposition-based methods have advantages in enhancing image details, they also have clear disadvantages, which include intensive computations, over-enhanced noise, and gradient reversal artifacts. In this paper, we propose to accelerate enhancement processing by using a fast guided filter and plateau equalization. Our method consists of image decomposition, base and detail layers processing, and projection of the enhanced image to an 8-bit dynamic range. Experimental results demonstrated that our proposed method achieves a good balance among detail enhancement performance, noise and gradient reversal artifacts suppression, and computational cost, with a frame rate around 30 fps for 640×512 infrared images.
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Source |
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http://dx.doi.org/10.1364/AO.396417 | DOI Listing |
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