Matches in SemOpenAlex for { <https://semopenalex.org/work/W3170647946> ?p ?o ?g. }
Showing items 1 to 80 of
80
with 100 items per page.
- W3170647946 abstract "The implementation of an image contrast enhancement algorithm along with artificial intelligence techniques can have various applications besides modern photography. It basically ameliorates the quality of low contrast images. The main focus of this research is developing a new image contrast enhancement method that combines the concept of artificial intelligence and histogram equalization techniques to provide a contrast distribution for the low contrast images by utilizing the classifier to prevent data loss from images. In this research an ANN based AHE algorithm for enhancement of low contrast images is proposed. The main objectives of this research is to study the existing digital image contrast enhancement techniques to find out the exact problems and to classify the level of contrast in a digital image as low or high, so as to ascertain whether enhancement is required or not. The concept of ANN with AHE is used here to find out the contrast level of the image before processing for contrast enhancement. For validation of the proposed ANN-AHE algorithm, a comparison with the existing techniques are performed on the behalf of performance parameters such as PSNR, MSE, Entropy, QI, QRCM, CQE, SSIM and Computational Time. The simulation of the proposed model is performed in MATLAB 2016a with the help of image processing and artificial neural network toolbox." @default.
- W3170647946 created "2021-06-22" @default.
- W3170647946 creator A5055249500 @default.
- W3170647946 creator A5080063282 @default.
- W3170647946 date "2021-03-17" @default.
- W3170647946 modified "2023-09-23" @default.
- W3170647946 title "An Artificial Neural Network based Adaptive Histogram Equalization Algorithm for Enhancement of Low Contrast Images" @default.
- W3170647946 cites W2520996069 @default.
- W3170647946 cites W2664998303 @default.
- W3170647946 cites W2773665420 @default.
- W3170647946 cites W2775213370 @default.
- W3170647946 cites W2913779569 @default.
- W3170647946 cites W2979332218 @default.
- W3170647946 doi "https://doi.org/10.1109/indiacom51348.2021.00047" @default.
- W3170647946 hasPublicationYear "2021" @default.
- W3170647946 type Work @default.
- W3170647946 sameAs 3170647946 @default.
- W3170647946 citedByCount "0" @default.
- W3170647946 crossrefType "proceedings-article" @default.
- W3170647946 hasAuthorship W3170647946A5055249500 @default.
- W3170647946 hasAuthorship W3170647946A5080063282 @default.
- W3170647946 hasConcept C11413529 @default.
- W3170647946 hasConcept C115961682 @default.
- W3170647946 hasConcept C126838900 @default.
- W3170647946 hasConcept C136943445 @default.
- W3170647946 hasConcept C143409427 @default.
- W3170647946 hasConcept C153180895 @default.
- W3170647946 hasConcept C154945302 @default.
- W3170647946 hasConcept C2776502983 @default.
- W3170647946 hasConcept C3018181011 @default.
- W3170647946 hasConcept C30387639 @default.
- W3170647946 hasConcept C31972630 @default.
- W3170647946 hasConcept C41008148 @default.
- W3170647946 hasConcept C50644808 @default.
- W3170647946 hasConcept C53533937 @default.
- W3170647946 hasConcept C71924100 @default.
- W3170647946 hasConcept C9417928 @default.
- W3170647946 hasConceptScore W3170647946C11413529 @default.
- W3170647946 hasConceptScore W3170647946C115961682 @default.
- W3170647946 hasConceptScore W3170647946C126838900 @default.
- W3170647946 hasConceptScore W3170647946C136943445 @default.
- W3170647946 hasConceptScore W3170647946C143409427 @default.
- W3170647946 hasConceptScore W3170647946C153180895 @default.
- W3170647946 hasConceptScore W3170647946C154945302 @default.
- W3170647946 hasConceptScore W3170647946C2776502983 @default.
- W3170647946 hasConceptScore W3170647946C3018181011 @default.
- W3170647946 hasConceptScore W3170647946C30387639 @default.
- W3170647946 hasConceptScore W3170647946C31972630 @default.
- W3170647946 hasConceptScore W3170647946C41008148 @default.
- W3170647946 hasConceptScore W3170647946C50644808 @default.
- W3170647946 hasConceptScore W3170647946C53533937 @default.
- W3170647946 hasConceptScore W3170647946C71924100 @default.
- W3170647946 hasConceptScore W3170647946C9417928 @default.
- W3170647946 hasLocation W31706479461 @default.
- W3170647946 hasOpenAccess W3170647946 @default.
- W3170647946 hasPrimaryLocation W31706479461 @default.
- W3170647946 hasRelatedWork W1592559668 @default.
- W3170647946 hasRelatedWork W1808341714 @default.
- W3170647946 hasRelatedWork W1996900070 @default.
- W3170647946 hasRelatedWork W2059832556 @default.
- W3170647946 hasRelatedWork W2062438821 @default.
- W3170647946 hasRelatedWork W2071396108 @default.
- W3170647946 hasRelatedWork W2146245390 @default.
- W3170647946 hasRelatedWork W2151525510 @default.
- W3170647946 hasRelatedWork W2253258865 @default.
- W3170647946 hasRelatedWork W2560439518 @default.
- W3170647946 hasRelatedWork W2753760751 @default.
- W3170647946 hasRelatedWork W2795290496 @default.
- W3170647946 hasRelatedWork W2906604762 @default.
- W3170647946 hasRelatedWork W2970794526 @default.
- W3170647946 hasRelatedWork W2998972693 @default.
- W3170647946 hasRelatedWork W3029795769 @default.
- W3170647946 hasRelatedWork W3117284242 @default.
- W3170647946 hasRelatedWork W3121744110 @default.
- W3170647946 hasRelatedWork W3129666728 @default.
- W3170647946 hasRelatedWork W3161216514 @default.
- W3170647946 isParatext "false" @default.
- W3170647946 isRetracted "false" @default.
- W3170647946 magId "3170647946" @default.
- W3170647946 workType "article" @default.