Image enhancement utilizes intensity transformation functions to maximize the information content of enhanced images.This paper approaches the topic as an optimization problem and uses the bald eagle search(BES)algori...Image enhancement utilizes intensity transformation functions to maximize the information content of enhanced images.This paper approaches the topic as an optimization problem and uses the bald eagle search(BES)algorithm to achieve optimal results.In our proposed model,gamma correction and Retinex address color cast issues and enhance image edges and details.The final enhanced image is obtained through color balancing.The BES algorithm seeks the optimal solution through the selection,search,and swooping stages.However,it is prone to getting stuck in local optima and converges slowly.To overcome these limitations,we propose an improved BES algorithm(ABES)with enhanced population learning,position updates,and control parameters.ABES is employed to optimize the core parameters of gamma correction and Retinex to improve image quality,and the maximization of information entropy is utilized as the objective function.Real benchmark images are collected to validate its performance.Experimental results demonstrate that ABES outperforms the existing image enhancement methods,including the flower pollination algorithm,the chimp optimization algorithm,particle swarm optimization,and BES,in terms of information entropy,peak signal-to-noise ratio(PSNR),structural similarity index(SSIM),and patch-based contrast quality index(PCQI).ABES demonstrates superior performance both qualitatively and quantitatively,and it helps enhance prominent features and contrast in the images while maintaining the natural appearance of the original images.展开更多
Froth image could strongly indicate the production status in mineral flotation process.Considering low contrast and sensitivity to noises and illumination of froth images in flotation cells,an improved image enhanceme...Froth image could strongly indicate the production status in mineral flotation process.Considering low contrast and sensitivity to noises and illumination of froth images in flotation cells,an improved image enhancement algorithm based on nonsubsampled contourlet transform (NSCT) and multiscale Retinex algorithm has been proposed.Nonsubsampled contourlet transform was firstly adopted to decompose the flotation froth images,ensure signals invariance and avoid the blurring edge.Secondly,a multiscale Retinex algorithm was used to enhance the lower frequency image and improve the brightness uniformity.Adaptive classification method based on Bayes atrophy threshold was proposed to eliminate noise,preserve strong edges,and enhance weak edges of band-pass sub-band images.Experiment shows that the proposed method could enhance the edge,contour,details and curb noise,and improve visual effects.Under-segmentation caused by noise and blurring edge has been solved,which lays a foundation for extracting foamy morphological flotation froth and analyzing grade.展开更多
基金supported by the Research on theKey Technology of Damage Identification Method of Dam Concrete Structure based on Transformer Image Processing(242102521031)the project Research on Situational Awareness and Behavior Anomaly Prediction of Social Media Based on Multimodal Time Series Graph(232102520004)Key Scientific Research Project of Higher Education Institutions in Henan Province(25B520019).
文摘Image enhancement utilizes intensity transformation functions to maximize the information content of enhanced images.This paper approaches the topic as an optimization problem and uses the bald eagle search(BES)algorithm to achieve optimal results.In our proposed model,gamma correction and Retinex address color cast issues and enhance image edges and details.The final enhanced image is obtained through color balancing.The BES algorithm seeks the optimal solution through the selection,search,and swooping stages.However,it is prone to getting stuck in local optima and converges slowly.To overcome these limitations,we propose an improved BES algorithm(ABES)with enhanced population learning,position updates,and control parameters.ABES is employed to optimize the core parameters of gamma correction and Retinex to improve image quality,and the maximization of information entropy is utilized as the objective function.Real benchmark images are collected to validate its performance.Experimental results demonstrate that ABES outperforms the existing image enhancement methods,including the flower pollination algorithm,the chimp optimization algorithm,particle swarm optimization,and BES,in terms of information entropy,peak signal-to-noise ratio(PSNR),structural similarity index(SSIM),and patch-based contrast quality index(PCQI).ABES demonstrates superior performance both qualitatively and quantitatively,and it helps enhance prominent features and contrast in the images while maintaining the natural appearance of the original images.
基金Project(61134006)supported by the National Natural Science Foundation of ChinaProject(2012BAF03B05)supported by the National Key Technology R&D Program of ChinaProject(11JJ6062)supported by Hunan Provincial Natural Science Foundation,China
文摘Froth image could strongly indicate the production status in mineral flotation process.Considering low contrast and sensitivity to noises and illumination of froth images in flotation cells,an improved image enhancement algorithm based on nonsubsampled contourlet transform (NSCT) and multiscale Retinex algorithm has been proposed.Nonsubsampled contourlet transform was firstly adopted to decompose the flotation froth images,ensure signals invariance and avoid the blurring edge.Secondly,a multiscale Retinex algorithm was used to enhance the lower frequency image and improve the brightness uniformity.Adaptive classification method based on Bayes atrophy threshold was proposed to eliminate noise,preserve strong edges,and enhance weak edges of band-pass sub-band images.Experiment shows that the proposed method could enhance the edge,contour,details and curb noise,and improve visual effects.Under-segmentation caused by noise and blurring edge has been solved,which lays a foundation for extracting foamy morphological flotation froth and analyzing grade.
