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General Adaptive Neighborhood Image Restoration, Enhancement and Segmentation [chapter]

Johan Debayle, Yann Gavet, Jean-Charles Pinoli
2006 Lecture Notes in Computer Science  
After a brief theoretical introductory survey, the GANIP approach will be successfully applied on real application examples in image restoration, enhancement and segmentation.  ...  These so-called General Adaptive Neighborhoods (GANs) are simultaneously adaptive with the spatial structures, the analyzing scales and the physical settings of the image to be addressed and/or the human  ...  Gain from the University Hospital Center of Saint-Etienne in France, who has kindly provided the human corneal endothelial images ( Fig. 5-a,b) .  ... 
doi:10.1007/11867586_3 fatcat:ot7emrkzv5cibgwrhnbd4rxgau

General Adaptive Neighborhood Image Processing for Biomedical Applications [chapter]

Johan Debayle, Jean-Charles Pinoli
2011 Applied Biomedical Engineering  
The authors would like to thank the different partners from the University Hospital Center of Saint-Etienne and from the LPMG CNRS Unit in France who have kindly supplied different original images studied  ...  in various biomedical fields, namely image restoration, enhancement and segmentation. 497 General Adaptive Neighborhood Image Processing for Biomedical Applications www.intechopen.com Different scales  ...  This restoration process is generally needed before segmenting and analyzing and measuring the regions of interest.  ... 
doi:10.5772/18614 fatcat:nj3ubgkl65cfvgmxra36juqlgy

General Adaptive Neighborhood Image Processing

Johan Debayle, Jean-Charles Pinoli
2006 Journal of Mathematical Imaging and Vision  
Gavet (ENSM.SE/CIS) for his encouragement and his computing contributions.  ...  : General Adaptive Neighborhood Image Processing GANMM : General Adaptive Neighborhood Mathematical Morphology GLIP : General Linear Image Processing LIP : Logarithmic Image Processing LRIP :  ...  Consequently, a specific kind of GANs, the Combined General Adaptive Neighborhoods (C-GANs) denoted Z f m (.), are introduced to enable images corrupted by such a noise to be restored.  ... 
doi:10.1007/s10851-006-7452-7 fatcat:ykil74qsrndx5cnwm7yoqjwvwi

Logarithmic Adaptive Neighborhood Image Processing (LANIP): Introduction, Connections to Human Brightness Perception, and Application Issues

J-C Pinoli, J Debayle
2006 EURASIP Journal on Advances in Signal Processing  
The proposed approach is called logarithmic adaptive neighborhood image processing (LANIP) since it is based on the logarithmic image processing (LIP) and on the general adaptive neighborhood image processing  ...  The LANIP approach is finally exposed in several areas: image multiscale decomposition, image restoration, image segmentation, and image enhancement, through biomedical materials and visual imaging applications  ...  Barral from the University Hospital Center of Saint-Etienne in France, who have kindly provided the human corneal endothelial images (Figures 9(a), 9(b) ) and the brain image damaged by a cerebrovascular  ... 
doi:10.1155/2007/36105 fatcat:wh2euvdunzdrtljv4cxejcsiey

Automatic Detection of Glaucoma based on Refined Complete Local Binary Pattern and Random Forest Classification Method

2019 VOLUME-8 ISSUE-10, AUGUST 2019, REGULAR ISSUE  
In the third step Statistical Optimized and Restoration model is use to extract the enhanced images using the restoration technique.  ...  The first step is use to convert a color image into gray scale image and the second step we use Neighborhood Fuzzy K Means Clustering to segment Optic Disc(OD) and Optic Cup(OC).  ...  In the third step Statistical Optimized and Restoration model is use to extract the enhanced images using the restoration technique.  ... 
doi:10.35940/ijitee.j1003.08810s19 fatcat:3roefbbxjbbtvo66sw32d2xk7q

Improvement of Sonographic Appearance Using HAT-TOP Methods

Yousif Mohamed Y. Abdallah
2018 Journal of Biomedical Engineering and Medical Imaging  
Many image-processing techniques were used to improve the images including Using HAT-TOP and Blind Deconvolution Algorithm.  ...  In ultrasound images, the recognition closely adjacent tissues is very crucial process because of the noise that affected both image quality and sharpness.  ...  Based on Wiener filter method considered as the adaptive Wiener filtering of noisy images and image sequences.  ... 
doi:10.14738/jbemi.55.5283 fatcat:mgpcqjzqrrcqnfbncq3r2armgi

A robust structural fingerprint restoration [chapter]

M. Hassan Ghassemian Yazdi
1997 Lecture Notes in Computer Science  
Fast and accurate segmentation of fingerprints is essential to each AFIS (Automatic Fingerprint Identification System).  ...  Smudged furrows and cut ridges in the image of a fingerprint is the major problem in any AFIS.  ...  Also, the structural information of finger patterns, as a grammar rule, is incorporated in the process to enhance the segmented image. The procedure is on line, unsupervised and adaptive.  ... 
doi:10.1007/3-540-63508-4_166 fatcat:asthomkp2zgh5bnabboknzcgpa

Feature Extraction of an Image by Using Adaptive Filtering and Morpological Segmentation

Anil kumar
2013 IOSR Journal of Electronics and Communication Engineering  
For enhancing an image various enhancement schemes are used which includes gray scale manipulation, filtering and Histogram Equalization, Where Histogram equalization is one of the well known image enhancement  ...  Here using morphological segmentation we can get the segmented image. Morphological reconstruction is used to segment the image.  ...  We use the Contrast limited adaptive Histogram Equalization (CLAHE) to enhance the medical images, and Morphological techniques for segment the Enhanced medical image. IV.  ... 
doi:10.9790/2834-0725964 fatcat:ghmr2uu35fc63g3fwua35hwoc4

Efficient thermal image segmentation through integration of nonlinear enhancement with unsupervised active contour model

Fatema A. Albalooshi, Evan Krieger, Paheding Sidike, Vijayan K. Asari, David Casasent, Mohammad S. Alam
2015 Optical Pattern Recognition XXVI  
The algorithm is tested on segmenting different objects in thermal images and it is observed that the nonlinear enhancement has significantly improved the segmentation performance.  ...  However, the lack of texture and color information, low signal-to-noise ratio, and blurring effect of thermal images make segmenting infrared heat patterns a challenging task.  ...  INTRODUCTION Image segmentation is a challenging task due to the reason that there is no generic solution that is suitable for all kinds of images and objects.  ... 
doi:10.1117/12.2179199 fatcat:3a4xkofpsrf3llh7gflzjz6fu4

The Beneficial Techniques in Preprocessing Step of Skin Cancer Detection System Comparing

Azadeh Noori Hoshyar, Adel Al-Jumaily, Afsaneh Noori Hoshyar
2014 Procedia Computer Science  
Preprocessing is the first stage of detection to improve the quality of images, removing the irrelevant noises and unwanted parts in the background of the skin images.  ...  Automatic diagnostics of skin cancer is one of the most challenging problems in medical image processing. It helps physicians to decide whether a skin melanoma is benign or malignant.  ...  It has classified the whole process into two sections of Image Enhancement and Image Restoration.  ... 
doi:10.1016/j.procs.2014.11.029 fatcat:etaf5io5ejahng5pm7fkxmmhri

Special issue on real-time color image processing

M. Emre Celebi, Bogdan Smolka, Gerald Schaefer
2015 Journal of Real-Time Image Processing  
In ''An Adaptive Dynamic Range Compression with Local Contrast Enhancement Algorithm for Real-Time Color Image Enhancement,'' Tsai and Huang propose a fast color image enhancement method that uses dynamic  ...  Trieu and Maruyama, in their work titled ''Real-Time Color Image Segmentation Based on Mean Shift Algorithm Using an FPGA,'' describe the details of a fast implementation of a well-known image segmentation  ... 
doi:10.1007/s11554-015-0506-6 fatcat:yc65ssxd3vdflasgshooc66yb4

Ensemble LUT classification for degraded document enhancement

Tayo Obafemi-Ajayi, Gady Agam, Ophir Frieder, Berrin A. Yanikoglu, Kathrin Berkner
2008 Document Recognition and Retrieval XV  
In contrast, we propose to estimate local degradation models and use them in enhancing degraded document images.  ...  Enhancement of degraded document images is normally performed assuming global degradation models. When the degradation is large, global degradation models do not perform well.  ...  We can generalize the cascade LUT classifier to comprise of m LUTs with a cost equivalent to m times the cost of training and using one LUT.  ... 
doi:10.1117/12.767120 dblp:conf/drr/Obafemi-AjayiAF08 fatcat:uophygx2lre5tijgzeexj56zwe

Adaptive image restoration based on hierarchical neural networks

Kim Hui Yap
2000 Optical Engineering: The Journal of SPIE  
The degraded image is first segmented and partitioned into smooth, texture, and edge clusters. It is then mapped onto a three-level HCM structure.  ...  The scheme progressively selects the well-evolved individuals that consist of partially restored images, their corresponding cluster structures, segmentation maps, and the optimized regularization vector  ...  The restored image using Katsaggelos and Kang's adaptive restoration 11 is given in Fig. 1͑d͒ .  ... 
doi:10.1117/1.602572 fatcat:bky5mdokovd7pbpqkaif67kare

Minimum Kurtosis CMA Deconvolution for Blind Image Restoration

Pradeepa D. Samarasinghe, Rodney A. Kennedy
2008 2008 4th International Conference on Information and Automation for Sustainability  
To our knowledge, no research has been done on the effect of source correlation on adaptive blind deblurring of images through CMA, and this paper addresses that gap, coming up with a novel model of addressing  ...  Index Terms-blind equalization, blind deconvolution, image processing, blind image restoration, Constant Modulus Algorithm, CMA, Godard algorithm, kurtosis.  ...  Based on this model of an image, we change our CMA adaptation system to adapt only on the segmented minimum kurtosis areas. Several tests were carried out to validate the model we propose.  ... 
doi:10.1109/iciafs.2008.4783974 fatcat:nr5v4lbwvnbsdikxws4m33lqeu

Enhancement of Degraded Manuscript Images using Adaptive Gaussian Thresholding

Nikunj Khetan, Lakshya Kejriwal, S. Indu
2017 International Journal of Future Generation Communication and Networking  
We propose a novel method to address the problem of enhancement and binarization of degraded manuscript images that applies a dual filtering technique for noise removal, Gaussian based adaptive thresholding  ...  technique and post processing using morphological operations that enhances readability of manuscript images.  ...  After Applying Mean Shift Filter Adaptive thresholding: In this stage, we apply thresholding to segment foreground from background and binarize the image.  ... 
doi:10.14257/ijfgcn.2017.10.1.05 fatcat:f7hdi3o6sngzhmkpakoxosrg2q
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