Relevant bibliographies by topics / Contrast limited adaptive histogram equalization (CLAHE)

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Academic literature on the topic 'Contrast limited adaptive histogram equalization (CLAHE)'

Author: Grafiati
Published: 4 June 2025
Last updated: 1 August 2025

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Journal articles on the topic "Contrast limited adaptive histogram equalization (CLAHE)"

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Yustiantara, Natanael Putra. "IMAGE ENHACEMENT PADA CITRA GESTUR TANGAN MENGGUNAKAN CONTRAST LIMITED ADAPTIVE HISTOGRAM EQUALIZATION." Joutica 6, no. 2 (2021): 454. http://dx.doi.org/10.30736/jti.v6i2.612.

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Image Enhacement merupakan proses perbaikan kualitas citra yang dilakukan dengan menggunakan beberapa metode. Citra yang paling sering dilakukan perbaikan kualitas adalah citra digital. Citra digital sering digunakan pada pengolahan citra biometrik, pengenalan wajah, pengenalan tanda tangan, bahkan permasalahan pada Closed Circuit Television (CCTV). Penelitian ini bertujuan untuk memberikan perbedaan hasil proses image enhacement pada gambar yang telah tertangkap oleh CCTV. Penelitian ini menggunakan 3 buah metode yaitu, Histogram Equalization (HE), Adaptive Histogram Equalization (AHE), dan C
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Abood, Loay Kadom. "Contrast enhancement of infrared images using Adaptive Histogram Equalization (AHE) with Contrast Limited Adaptive Histogram Equalization (CLAHE)." Iraqi Journal of Physics (IJP) 16, no. 37 (2018): 127–35. http://dx.doi.org/10.30723/ijp.v16i37.84.

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The objective of this paper is to improve the general quality of infrared images by proposes an algorithm relying upon strategy for infrared images (IR) enhancement. This algorithm was based on two methods: adaptive histogram equalization (AHE) and Contrast Limited Adaptive Histogram Equalization (CLAHE). The contribution of this paper is on how well contrast enhancement improvement procedures proposed for infrared images, and to propose a strategy that may be most appropriate for consolidation into commercial infrared imaging applications.The database for this paper consists of night vision i
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GuruKesavaDasu, Dr Gopisetty. "Local Adaptive Image Equalization." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 04 (2024): 1–5. http://dx.doi.org/10.55041/ijsrem29906.

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This paper presents a comprehensive approach to image enhancement, targeting the enhancement of contrast and reduction of noise in digital images. Leveraging state-of-the-art algorithms, the proposed methodology encompasses a strategic pipeline. Initially, the images undergo Histogram Equalization, a fundamental technique, to globally enhance contrast. Building upon this foundation, Contrast Limited Adaptive Histogram Equalization (CLAHE) is applied to achieve localized contrast enhancement, ensuring optimal balance and preservation of image details. Furthermore, the Adaptive Gamma Correction
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Ng, Yu Jie, and Kok Swee Sim. "A Review of Brain Early Infarct Image Contrast Enhancement Using Various Histogram Equalization Techniques." International Journal on Advanced Science, Engineering and Information Technology 14, no. 6 (2024): 1849–60. https://doi.org/10.18517/ijaseit.14.6.10115.

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Stroke is one of the leading causes of death worldwide, accounting for five of all deaths in Malaysia. It happens when an infarct from a blocked blood artery results in brain necrosis. Diagnoses involving brain diseases and injuries can be made with the help of CT scans, which create axial images by using exact X-ray measurements. These scans offer vital information on the anatomy and physiology of the brain. For an appropriate diagnosis, early infarct brain CT scan contrast can be improved. The two main types of histogram equalization (HE) approaches used for this purpose are Global Histogram
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Fousia, M. Shamsudeen, and Raju G. "A novel equalization scheme for the selective enhancement of optical disc and cup regions and background suppression in fundus imagery." TELKOMNIKA Telecommunication, Computing, Electronics and Control 17, no. 4 (2019): 1715–22. https://doi.org/10.12928/TELKOMNIKA.v17i4.5364.

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The ratio of the diameters of Optic Cup (OC) and Optic Disc (OD), termed as ‘Cup to Disc Ratio’ (CDR), derived from the fundus imagery is a popular biomarker used for the diagnosis of glaucoma. Demarcation of OC and OD either manually or through automated image processing algorithms is error prone because of poor grey level contrast and their vague boundaries. A dedicated equalization which simultaneously compresses the dynamic range of the background and stretches the range of ODis proposed in this paper. Unlike the conventional GHE, in the proposed equalization, the original hist
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Mohd-Isa, Wan-Noorshahida, Joel Joseph, Noramiza Hashim, and Nbhan Salih. "Enhancement of digitized X-ray films using Contrast-Limited Adaptive Histogram Equalization (CLAHE)." F1000Research 10 (October 15, 2021): 1051. http://dx.doi.org/10.12688/f1000research.73236.1.

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Background: Rural clinics still have X-ray facilities that produce physical films, which are sent to the nearest hospital for evaluation. Purchasing digitalization facilities is costly, thus, sending digitized films to the radiologist may be a solution. This can be achieved via digital photo capture. However, there can be different output resolutions that may not be optimized for online diagnosis. This paper investigates if digitized X-ray films can be enhanced using image processing techniques of Contrast-Limited Adaptive Histogram Equalization (CLAHE), Normalized-CLAHE (N-CLAHE) and Min-Max
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Farah, F. Alkhalid, Mudher Hasan Ahmed, and A. Alhamady Ahmed. "Improving radiographic image contrast using multi layers of histogram equalization technique." International Journal of Artificial Intelligence (IJ-AI) 10, no. 1 (2021): 151–56. https://doi.org/10.11591/ijai.v10.i1.pp151-156.

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Usually, X-ray image has distortion in many parts because it is focusing on bones rather than other, However, when dentist needs to make decision analysis, he does that by using X-ray and many opinions can be judged by looking closely on it like (inflammation, infection, tooth nerve, root of the tooth…). This paper proposes on new suggested technique by applying multilayers of histogram equalization (HE) and contrast limited adaptive histogram equalization (CLAHE) in order to make high contrast of X-ray, this technique provides very satisfied results and smooth intensity which leads to
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Suharyanto, Suharyanto, and Frieyadie Frieyadie. "ANALISIS KOMPARASI PERBAIKAN KUALITAS CITRA BAWAH AIR BERBASIS KONTRAS PEMERATAAN HISTOGRAM." INTI Nusa Mandiri 15, no. 1 (2020): 95–102. http://dx.doi.org/10.33480/inti.v15i1.1501.

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Dalam makalah ini, penulis melakukan komparasi metode pemerataan histogram yang biasa digunakan untuk meningkatkan citra. Gambar bawah air umumnya mengalami penurunan kontras yang cukup rendah dan kualitas bayangan yang menurun. Saat kita melakukan penangkapan gambar dari udara ke air, keseluruhan gambar akan mengalami perubahan. Selama menangkap beberapa efek absorpsi, refleksi dan hamburan diinduksi dalam bentuk kontras, kualitas, dan noise saat gambar terlihat tidak jelas atau kabur. Ini membuat gambar dipenuhi satu bayangan. Untuk mengatasi faktor-faktor tersebut dan penggunaan sumber daya
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Yu, Cheng Yi, Hsueh Yi Lin, and Cheng Jian Lin. "Image Contrast Enhancement by Hybrid 3SAIHT and CLAHE Algorithm." Applied Mechanics and Materials 479-480 (December 2013): 870–77. http://dx.doi.org/10.4028/www.scientific.net/amm.479-480.870.

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Human visual perception is insensitive to certain shades of gray but can distinguish among 20 to 30 shades of gray under a given adaptation level. In this paper, we propose an image fusion pipeline that generates a high vision quality image by fusing the Three-Scale Adaptive Inverse Hyperbolic Tangent (3SAIHT) and the Contrast-Limited Adaptive Histogram Equalization (CLAHE) algorithms to increase detail and edge information. Fusion results are clearer and better with regard to display quality and contrast enhancement.
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Khan, Sajid Ali, Shariq Hussain, and Shunkun Yang. "Contrast Enhancement of Low-Contrast Medical Images Using Modified Contrast Limited Adaptive Histogram Equalization." Journal of Medical Imaging and Health Informatics 10, no. 8 (2020): 1795–803. http://dx.doi.org/10.1166/jmihi.2020.3196.

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The low contrast medical images seriously affect the clinical diagnosis process. To improve the image quality, we propose an effective medical images contrast enhancement technique in this paper. Shear wavelet transformation is used for decomposition of image components into low-frequency and high-frequency. The low-frequency part contrast is adjusted by applying modified contrast limited adaptive histogram equalization (CLAHE). The resultant image is further processed through technique of fuzzy contrast enhancement to maintain the spectral information of an image. Results of the experimentati
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Dissertations / Theses on the topic "Contrast limited adaptive histogram equalization (CLAHE)"

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Mallampati, Vivek. "Image Enhancement & Automatic Detection of Exudates in Diabetic Retinopathy." Thesis, Blekinge Tekniska Högskola, Institutionen för tillämpad signalbehandling, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-18109.

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Diabetic retinopathy (DR) is becoming a global health concern, which causes the loss of vision of most patients with the disease. Due to the vast prevalence of the disease, the automated detection of the DR is needed for quick diagnoses where the progress of the disease is monitored by detection of exudates changes and their classifications in the fundus retina images. Today in the automated system of the disease diagnoses, several image enhancement methods are used on original Fundus images. The primary goal of this thesis is to make a comparison of three of popular enhancement methods of the
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CHEN, ZHI-FAN, and 陳志凡. "An Image Enhancement Method Based on Bilateral Filtering and Contrast Limited Adaptive Histogram Equalization." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/77m8t9.

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碩士<br>國立中正大學<br>資訊管理系研究所<br>104<br>At present, digital photography technology can’t be precisely presented as the scene seen by the human eye since the display device is typically low dynamic range rather than high dynamic range. In other words, the devices are often unable to display the details of shadows and highlights at the same time for high contrast images. If a normal image enhancement method is used to enhance these images, it may result in uneven distribution of image brightness, color distortion or loss of image detail information. Therefore, this study proposes a method to resolve
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Fan, Chao. "Real-time facial expression analysis : a thesis presented in partial fulfillment of the requirements for the degree of Doctor of Philosophy (Ph.D.) in Computer Science at Massey University, Auckland, New Zealand." 2008. http://hdl.handle.net/10179/762.

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As computers have become more and more advanced, with even the most basic computer capable of tasks almost unimaginable only a decade ago, researchers and developers are focusing on improving the way that computers interact with people in their everyday lives. A core goal, therefore, is to develop a computer system which can understand and react appropriately to natural human behavior. A key requirement for such a system is the ability to automatically, and in real time, recognises human facial expressions. In addition, this must be successfully achieved regardless of the inherent differences
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Βλαχοκώστα, Αλεξάνδρα. "Ανάπτυξη τεχνικών επεξεργασίας ιατρικών δεδομένων και συστημάτων υποστήριξης της διάγνωσης στη γυναικολογία". Thesis, 2014. http://hdl.handle.net/10889/8537.

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Η αυτόματη επεξεργασία εικόνων του ενδομητρίου αποτελεί ένα δύσκολο και πολυδιάστατο πρόβλημα, το οποίο έχει απασχολήσει πλήθος ερευνητών και για το οποίο έχει αναπτυχθεί μεγάλος αριθμός τεχνικών. Στην παρούσα διατριβή, παρουσιάζεται μια μεθοδολογική προσέγγιση, η οποία βασίζεται στη χρήση αλγορίθμων ψηφιακής επεξεργασίας και ανάλυσης εικόνων, για την αυτόματη εκτίμηση χαρακτηριστικών που περιγράφουν την αγγείωση και την υφή εικόνων του ενδομητρίου. Αφορμή της μελέτης αποτελεί ο ρόλος που διαπιστώνεται ότι διαδραματίζει η μεταβολή των τιμών των εν λόγω χαρακτηριστικών στην έγκαιρη διάγνωση τ
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Books on the topic "Contrast limited adaptive histogram equalization (CLAHE)"

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Rangarajan, Vidhya Ganesh. Effectiveness of Contrast Limited Adaptive Histogram Equalization on Multispectral Satellite Imagery. GRIN Verlag GmbH, 2018.

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Book chapters on the topic "Contrast limited adaptive histogram equalization (CLAHE)"

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Devi, D. Anjani Suputri, D. Sasi Rekha, Mudugu Kishore Kumar, P. Rama Mohana Rao, and G. Naga Vallika. "Transfer Learning-Based Effective Facial Emotion Recognition Using Contrast Limited Adaptive Histogram Equalization (CLAHE)." In Lecture Notes in Electrical Engineering. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-6690-5_20.

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Surya, S., and A. Muthukumaravel. "Adaptive Sailfish Optimization-Contrast Limited Adaptive Histogram Equalization (ASFO-CLAHE) for Hyperparameter Tuning in Image Enhancement." In Computational Intelligence for Clinical Diagnosis. Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-23683-9_5.

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Saravanan, P., and K. Vadivazhagan. "Underwater Image Classification with Sloth-Enhanced Contrast Limited Adaptive Histogram Equalization (S-CLAHE) and Deep Learning Algorithms." In Communications in Computer and Information Science. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-86296-0_3.

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Mohan, Shelda, and M. Ravishankar. "Modified Contrast Limited Adaptive Histogram Equalization Based on Local Contrast Enhancement for Mammogram Images." In Mobile Communication and Power Engineering. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-35864-7_60.

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Jain, Ayushi, Neha Mittal, and Shubham Nain. "CNN-based Recognition of Skin Cancer Using Contrast Limited Adaptive Histogram Equalization." In Micro-Electronics and Telecommunication Engineering. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-19-9512-5_61.

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Garima Yadav, Saurabh Maheshwari, and Anjali Agarwal. "Multi-domain Image Enhancement of Foggy Images Using Contrast Limited Adaptive Histogram Equalization Method." In Proceedings of the International Conference on Recent Cognizance in Wireless Communication & Image Processing. Springer India, 2016. http://dx.doi.org/10.1007/978-81-322-2638-3_4.

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Kuran, Umut, Emre Can Kuran, and Mehmet Bilal Er. "Parameter Selection of Contrast Limited Adaptive Histogram Equalization Using Multi-Objective Flower Pollination Algorithm." In Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-01984-5_9.

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Muneeswaran, V., and M. Pallikonda Rajasekaran. "Local Contrast Regularized Contrast Limited Adaptive Histogram Equalization Using Tree Seed Algorithm—An Aid for Mammogram Images Enhancement." In Smart Intelligent Computing and Applications. Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-1921-1_67.

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Quach, Luyl-Da, Phuc Nguyen Trong, Khang Nguyen Hoang, and Ngon Nguyen Chi. "Combining Contrast Limited Adaptive Histogram Equalization and Canny’s Algorithm for the Problem of Counting Seeds on Rice." In Smart Innovation, Systems and Technologies. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-19-7447-2_50.

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Madhavi, N., T. Srilakshmi, M. Swetha, Ch Bhavani, and T. Rama Rao. "Constructing and Developing Contrast-Limited Adaptive Histogram Equalization Method to Improve PSNR and UIQI Parameters in MRI Images Compared to Median Filtering." In Recent Developments in Microbiology, Biotechnology and Pharmaceutical Sciences. CRC Press, 2025. https://doi.org/10.1201/9781003618140-91.

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Conference papers on the topic "Contrast limited adaptive histogram equalization (CLAHE)"

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Alpan, Kezban, Bardia Arman, and Kamil Dimililer. "Effect of Contrast Limited Adaptive Histogram Equalization (CLAHE) on Breast Cancer Detection Using Residual Network (ResNet)." In 2025 1st International Conference on Computational Intelligence Approaches and Applications (ICCIAA). IEEE, 2025. https://doi.org/10.1109/icciaa65327.2025.11013776.

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Colney, Laldinpuii, Sandeep Kumar, and Arathy Rajeev. "Image Enhancement Using Color Balance and Contrast Limited Adaptive Histogram Equalization." In 2024 4th International Conference on Sustainable Expert Systems (ICSES). IEEE, 2024. https://doi.org/10.1109/icses63445.2024.10763082.

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Erukala, Mahender, and Suresh Kumar Sanampudi. "Lumbar Spine MRI Images Quality Enhancement through Contrast Limited Adaptive Histogram Equalization." In 2024 5th International Conference on Communication, Computing & Industry 6.0 (C2I6). IEEE, 2024. https://doi.org/10.1109/c2i663243.2024.10894837.

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Kurinjimalar, R., J. Pradeep, and M. Harikrishnan. "Underwater Image Enhancement Using Gaussian Pyramid, Laplacian Pyramid and Contrast Limited Adaptive Histogram Equalization." In 2024 IEEE 3rd World Conference on Applied Intelligence and Computing (AIC). IEEE, 2024. http://dx.doi.org/10.1109/aic61668.2024.10730935.

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Muralidhar, Nanditha, Vasuki Shankar, and Kc Narendra. "Assessing the Effectiveness of Contrast Limited Adaptive Histogram Equalization with DeepLabV3+ in Brain Tumor Segmentation." In 2025 International Conference on Knowledge Engineering and Communication Systems (ICKECS). IEEE, 2025. https://doi.org/10.1109/ickecs65700.2025.11035745.

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Kolluri, Johnson, and Ranjita Das. "Expression of Concern for: An efficient Synergic Model with Contrast Limited Adaptive Histogram Equalization model for Object Classification in Ship Detection." In 2022 IEEE 2nd Mysore Sub Section International Conference (MysuruCon). IEEE, 2022. http://dx.doi.org/10.1109/mysurucon55714.2022.10703500.

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Ferguson, Phillip David, Tughrul Arslan, Ahmet T. Erdogan, and Andrew Parmley. "Evaluation of contrast limited adaptive histogram equalization (CLAHE) enhancement on a FPGA." In 2008 IEEE International SOC Conference (SOCC). IEEE, 2008. http://dx.doi.org/10.1109/socc.2008.4641492.

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Zheng, Ruizhi, Qing Guo, Chang Gao, and Ming-an Yu. "A Hybrid Contrast Limited Adaptive Histogram Equalization (CLAHE) for Parathyroid Ultrasonic Image Enhancement." In 2019 Chinese Control Conference (CCC). IEEE, 2019. http://dx.doi.org/10.23919/chicc.2019.8866479.

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Kharel, Nabin, Abeer Alsadoon, P. W. C. Prasad, and A. Elchouemi. "Early diagnosis of breast cancer using contrast limited adaptive histogram equalization (CLAHE) and Morphology methods." In 2017 8th International Conference on Information and Communication Systems (ICICS). IEEE, 2017. http://dx.doi.org/10.1109/iacs.2017.7921957.

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Hendrawan, Aria, and Siti Asmiatun. "Identification of Picnosis Cells Using Contrast-Limited Adaptive Histogram Equalization (CLAHE) and K-means Algorithm." In 2018 1st International Conference on Computer Applications & Information Security (ICCAIS). IEEE, 2018. http://dx.doi.org/10.1109/cais.2018.8441978.

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