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

Author: Grafiati

Published: 4 June 2025

Last updated: 1 August 2025

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1

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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9

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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Sari, Ni Larasati Kartika, Maria Oktavianti, and Samsun Samsun. "Analisis Karakter Segmen Abnormal pada Citra Mamografi dengan Menggunakan Berbagai Metode Preprocessing Citra." Jurnal Ilmiah Giga 22, no. 1 (2020): 1. http://dx.doi.org/10.47313/jig.v22i1.737.

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Penelitian ini menganalisis pengaruh penerapan beberapa jenis algoritma preprocessing untuk mencari karakteristik segmen abnormal yang tampak pada citra mamografi. Mamografi merupakan pemeriksaan radiografi khusus payudara. Penerapan algoritma preprocessing yang terdiri dari metode filtering, contrast enhancement, sharpening, dan smoothing diharapkan dapat mengurangi noise dan meningkatkan kontras citra mamografi serta membantu ahli radiologi untuk melakukan diagnosis pada citra. Pada penelitian ini akan digunakan dua algoritma filtering yaitu median filter dan gaussian filter. Selain itu digu

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Andrikevych, S. A., and S. Yu Tuzhanskyi. "Improved method of adaptive histogram equalization for color fundus images." Optoelectronic Information-Power Technologies 49, no. 1 (2025): 82–88. https://doi.org/10.31649/1681-7893-2025-49-1-82-88.

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The paper investigates the improvement of the visualization quality of color fundus images using the contrast-limited adaptive histogram equalization (CLAHE) method. The method is applied to the R, G, B channels of images from the HRF database. The results showed an increase in the average contrast, and visual analysis confirmed better visibility of fundus vessels while preserving local details. The proposed approach is effective for image preprocessing in medical diagnostics. The proposed CLAHE method by separately processing the R, G, B channels has demonstrated its effectiveness in enhancin

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Nuraisha, Safira, and Sri Handayani. "ANALISIS IMPLEMENTASI CONTRAST LIMITED ADAPTIVE HISTOGRAM EQUALIZATION (CLAHE) UNTUK DETEKSI CITRA SIDIK JARI TIRUAN." Djtechno Jurnal Teknologi Informasi 2, no. 1 (2021): 38–44. http://dx.doi.org/10.46576/djtechno.v2i1.1255.

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Autentikasi biometrik dengan sidik jari paling sering digunakan untuk sistem keamanan atau autentikasi sebuah akun. Seiring dengan berkembangnya model sistem keamanan menggunakan autentikasi sidik jari, muncul masalah baru yaitu penggunaan sidik jari Penggunaan sidik jari palsu dapat dilakukan melalui scanner sidik jari yang menerima salinan dari sidik jari asli yang sering disebut dengan artificial fingerprints. Penggunaan sidik jari palsu dapat mengancam keamanan dari sebuah sistem. Permasalahan deteksi sidik jari dan identifikasi bahan yang dapat meniru karakteristik sidik jari diperburuk o

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Wanling, Wu, and Noraisyah Mohamed Shah. "Fundus Image Enhancement using CLAHE." Journal of New Explorations in Electrical Engineering 1, no. 1 (2025): 67–78. https://doi.org/10.22452/nece.vol1no1.6.

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Fundus retinal images are crucial for ophthalmologists to diagnose diseases and monitor changes in the condition. However, due to factors such as lighting conditions, instrument effects, and individual differences, fundus images often have the drawbacks of low contrast and lack of details. To improve the quality and accuracy of images, contrast enhancement technology for fundus images has become a research hotspot. This paper proposes a new CLAHE (Contrast Limited Adaptive Histogram Equalization) method to improve the brightness and contrast of retinal images. The method improves the luminosit

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Nasir, Ahmad Lutfi Afifi Mohd, Roslan Umar, Wan Nural Jawahir Wan Yussof, et al. "Comparative Analysis of Image Processing Technique in Determining the New Crescent Moon Visibility." Journal of Physics: Conference Series 2915, no. 1 (2024): 012004. https://doi.org/10.1088/1742-6596/2915/1/012004.

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Abstract This research presents a comparative analysis of advanced image processing techniques to enhance the visibility of the new crescent moon, a crucial element in astronomy and the lunar calendar. The primary objective is to assess the effectiveness of Contrast Adjustment (CA), Histogram Equalization (HE), Contrast Limited Adaptive Histogram Equalization (CLAHE), and Gamma Correction (GC) in improving new crescent moon visibility. The study utilized a comprehensive dataset of new crescent moon images captured on various dates and times, with each image undergoing a specific image processi

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Kenyta, Claudia, and Daniel Martomanggolo Wonohadidjojo. "Perbandingan Performa Histogram Equalization untuk Peningkatan Kualitas Gambar Minim Cahaya pada Android." Ultimatics : Jurnal Teknik Informatika 12, no. 2 (2020): 80–88. http://dx.doi.org/10.31937/ti.v12i2.1667.

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When the photos are taken in low light condition, the quality of the results will not meet their expectation. Image Enhancement method can be used to enhance the quality of the photos taken in low light condition. One of the algorithms used is called Histogram Equalization (HE), that works using Histogram basis. The superiority of HE algorithm in enhancing the quality of the photos taken in low light condition is the simplicity of the algorithm itself and it does not need a high specification device for the algorithm to run. One variant of HE algorithm is Contrast Limited Adaptive Histogram Eq

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Wu, Shibin, Shaode Yu, Yuhan Yang, and Yaoqin Xie. "Feature and Contrast Enhancement of Mammographic Image Based on Multiscale Analysis and Morphology." Computational and Mathematical Methods in Medicine 2013 (2013): 1–8. http://dx.doi.org/10.1155/2013/716948.

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A new algorithm for feature and contrast enhancement of mammographic images is proposed in this paper. The approach bases on multiscale transform and mathematical morphology. First of all, the Laplacian Gaussian pyramid operator is applied to transform the mammography into different scale subband images. In addition, the detail or high frequency subimages are equalized by contrast limited adaptive histogram equalization (CLAHE) and low-pass subimages are processed by mathematical morphology. Finally, the enhanced image of feature and contrast is reconstructed from the Laplacian Gaussian pyrami

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Kalaivani., N., Mozhi. N. Kani, M. Kanimozhi., S. Kalieswari., and R. Kuralarasi. "Endomicroscopy Image Recognition using Ensemble Neural network with Contrast Limited Adaptive Histogram Equalisation." International Journal of Engineering and Advanced Technology (IJEAT) 9, no. 4 (2020): 44–49. https://doi.org/10.35940/ijeat.C6438.049420.

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Endomicroscopy is a small tool used for cancer diagnosis, this enables in-vivo imaging at microscopic resolution closely to histology image during endoscopic procedures and captured image within the dataset has high imaging quality resulting in an inequality between moral and poor-quality images. There's no clear demonstration of the artifacts in an endomicroscopy producer. During this proposed method, the ensemble neural network (ENN) approach models to scale back the variance of predictions and reduce generalization error with contrast limited adaptive histogram equalization (CLAHE) algo

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Werdiningsih, Indah, Ira Puspitasari, and Rimuljo Hendradi. "Recognizing Daily Activities of Children with Autism Spectrum Disorder Using Convolutional Neural Network Based on Image Enhancement." Cybernetics and Information Technologies 25, no. 1 (2025): 78–96. https://doi.org/10.2478/cait-2025-0005.

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Abstract Independence for individuals with disabilities, Children with Autism Spectrum Disorder (ASD), need skills to perform daily activities. This study focuses on recognizing the daily activities of children with ASD using a Convolutional Neural Network (CNN) based on augmented images. The CNN architectures employed are Visual Geometry Group 19 (VGG19) and MobileNetV2, while image improvement techniques include Histogram Equalization, Contrast Stretching, and Contrast Limited Adaptive Histogram Equalization (CLAHE). The data consists of eating (606 videos) and drinking (477 videos) activiti

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Saifullah, Shoffan. "ANALISIS PERBANDINGAN HE DAN CLAHE PADA IMAGE ENHANCEMENT DALAM PROSES SEGMENASI CITRA UNTUK DETEKSI FERTILITAS TELUR." Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) 9, no. 1 (2020): 134. http://dx.doi.org/10.23887/janapati.v9i1.23013.

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Perkembangan teknologi di bidang peternakan mampu memberikan kemudahan dalam proses penetasan ayam. Namun, proses deteksi fertilitas telur telah diperiksa secara manual oleh pekerja yang menyortir telur yang fertil dan infertil. Penelitian ini bertujuan untuk mempermudah proses pendeteksian gambar fertilitas telur menggunakan sistem komputerisasi secara otomatis. Deteksi fertilitas telur dilakukan preprocessing dengan metode Image Enhancement. Dalam metode ini, metode Histogram Equalization (HE) dan metode Contrast Limited Adaptive Histogram Equalization (CLAHE) dibandingkan satu sama lain pad

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R, Priyah R., and S. Kamalakkannan. "Hybrid contrast-limited adaptive histogram equalization and Deep Learning techniques for improving liver tumor detection." Future Technology 4, no. 3 (2025): 67–75. https://doi.org/10.55670/fpll.futech.4.3.7.

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Deep Learning and advanced image processing can enhance the detection and prognosis of liver cancer using medical imaging, such as Magnetic Resonance Imaging (MRI) and Computed Tomography (CT) scans. Liver cancer detection is a challenging task due to factors such as poor contrast, noise in imaging techniques, limited annotated datasets, and the complex characteristics of tumors. This study proposes a hybrid technique that combines Contrast-Limited Adaptive Histogram Equalization (CLAHE), Convolutional Neural Networks (CNNs), Generative Adversarial Networks (GANs), and Transfer Learning (TL) t

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Hana, F. M., and I. D. Maulida. "Analysis of contrast limited adaptive histogram equalization (CLAHE) parameters on finger knuckle print identification." Journal of Physics: Conference Series 1764, no. 1 (2021): 012049. http://dx.doi.org/10.1088/1742-6596/1764/1/012049.

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Reza, Ali M. "Realization of the Contrast Limited Adaptive Histogram Equalization (CLAHE) for Real-Time Image Enhancement." Journal of VLSI Signal Processing-Systems for Signal, Image, and Video Technology 38, no. 1 (2004): 35–44. http://dx.doi.org/10.1023/b:vlsi.0000028532.53893.82.

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F. Alkhalid, Farah, Ahmed Mudher Hasan, and Ahmed A. Alhamady. "Improving radiographic image contrast using multi layers of histogram equalization technique." IAES International Journal of Artificial Intelligence (IJ-AI) 10, no. 1 (2021): 151. http://dx.doi.org/10.11591/ijai.v10.i1.pp151-156.

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<span id="docs-internal-guid-43432eef-7fff-9949-6deb-865191ff0740"><span>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

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Tinaliah, Tinaliah, and Triana Elizabeth. "Peningkatan Kualitas Citra X-Ray Paru-Paru Pasien Covid-19 Menggunakan Metode Contrast Limited Adaptive Histogram Equalization." Jurnal Teknologi Informasi 4, no. 2 (2020): 345–49. http://dx.doi.org/10.36294/jurti.v4i2.1709.

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Abstract - Covid-19 is currently a pandemic around the world, and until now there has been no specific cure for this disease. An x-ray examination of the lungs is one of the tests that can be done to detect Covid-19. X-ray results must be read carefully to determine whether the patient is really exposed to Covid-19. Improved quality of x-ray images is needed to help doctors or health practitioners see more clearly the x-ray results of the lungs. One of the methods used to improve image quality is the CLAHE method. This method is a simple and efficient method to implement and is able to produce

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Marciniak, Tomasz, and Agnieszka Stankiewicz. "Impact of Histogram Equalization on the Classification of Retina Lesions from OCT B-Scans." Electronics 13, no. 24 (2024): 4996. https://doi.org/10.3390/electronics13244996.

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Deep learning solutions can be used to classify pathological changes of the human retina visualized in OCT images. Available datasets that can be used to train neural network models include OCT images (B-scans) of classes with selected pathological changes and images of the healthy retina. These images often require correction due to improper acquisition or intensity variations related to the type of OCT device. This article provides a detailed assessment of the impact of preprocessing on classification efficiency. The histograms of OCT images were examined and, depending on the histogram dist

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Archana B and K. Kalirajan. "Contrast Enhancement of Alzheimer’s MRI using Histogram Analysis." Journal of Innovative Image Processing 5, no. 4 (2023): 379–89. http://dx.doi.org/10.36548/jiip.2023.4.003.

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Contrast enhancement of MRI images frequently needs considerable pre-processing to provide accurate data for disease diagnosis and proper treatment. Enhancing the appearance of medical images becomes a difficult task owing to the uncertainty of the obtained image quality. In this study, Alzheimer’s MRI images are subjected to a contrast enhancement algorithm for easy diagnosis. A noise reduction and contrast enhancement technique for MRI images is discussed in this research. Histogram-based algorithms are used to solve the problems of de-noising and enhancing the contrast of images for identif

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Saifullah, Shoffan, Andri Pranolo, and Rafał Dreżewski. "Comparative analysis of image enhancement techniques for braintumor segmentation: contrast, histogram, and hybrid approaches." E3S Web of Conferences 501 (2024): 01020. http://dx.doi.org/10.1051/e3sconf/202450101020.

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This study systematically investigates the impact of image enhancement techniques on Convolutional Neural Network (CNN)-based Brain Tumor Segmentation, focusing on Histogram Equalization (HE), Contrast Limited Adaptive Histogram Equalization (CLAHE), and their hybrid variations. Employing the U-Net architecture on a dataset of 3064 Brain MRI images, the research delves into preprocessing steps, including resizing and enhancement, to optimize segmentation accuracy. A detailed analysis of the CNN-based U-Net architecture, training, and validation processes is provided. The comparative analysis,

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Udayana, I. Putu Agus Eka Darma, I. Made Karang Satria Prawira, and I. Gede Bagus Arya Merta Tika. "Comparison of Artificial Intelligence Methods for Tuberculosis Detection Using X-Ray Images." IJCCS (Indonesian Journal of Computing and Cybernetics Systems) 19, no. 1 (2025): 49. https://doi.org/10.22146/ijccs.102601.

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Penyakit tuberkulosis (TB), yang disebabkan oleh bakteri Mycobacterium tuberculosis, merupakan penyakit menular yang sangat berbahaya. Di Indonesia, TB adalah penyakit menular paling mematikan setelah COVID-19 dan menempati urutan ke-13 sebagai penyebab kematian global. Deteksi dini TB sangat penting untuk meningkatkan peluang kesembuhan, namun keterbatasan jumlah ahli radiologi menjadi tantangan utama. Teknologi deep learning, khususnya Convolutional Neural Network (CNN), mejadi solusi efektif untuk masalah ini. Oleh karena itu, pada penelitian ini akan membandingkan dua arsitektur CNN, yaitu

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Saifullah, Shoffan. "Segmentasi Citra Menggunakan Metode Watershed Transform Berdasarkan Image Enhancement Dalam Mendeteksi Embrio Telur." Systemic: Information System and Informatics Journal 5, no. 2 (2020): 53–60. http://dx.doi.org/10.29080/systemic.v5i2.798.

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Image processing dapat diterapkan dalam proses deteksi embrio telur. Proses deteksi embrio telur dilakukan dengan menggunakan proses segmentasi, yang membagi citra sesuai dengan daerah yang dibagi. Proses ini memerlukan perbaikan citra yang diproses untuk memperoleh hasil optimal. Penelitian ini akan menganalisis deteksi embrio telur berdasarkan image processing dengan image enhancement dan konsep segmentasi menggunakan metode watershed transform. Image enhacement pada preprocessing dalam perbaikan citra menggunakan kombinasi metode Contrast Limited Adaptive Histogram Equalization (CLAHE) dan

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Sai, Varkala Tarun, Nallam Eswara Sai Akhil, Tandra Jaya Mallika Jashnavi, and Naga Venkata Kashim Kanakala. "Image Quality Enhancement for Wheat rust Diseased Leaf Image using Histogram Equalization & CLAHE." E3S Web of Conferences 391 (2023): 01029. http://dx.doi.org/10.1051/e3sconf/202339101029.

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In the domain of agriculture, few crops play an important role as wheat is one of them. It is one of the most important one’s across the globe. Nearly providing 15% food production across the world, it is also a winter cereal crop and a most essential food. The real challenge is to enhance the images of wheat crop in the agricultural area. because some of these are captured in real space environments may not be that clear to predict the type of disease of the crop that it is suffering from. So, we enhance the captured images using few existing techniques using the image histograms and the furt

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Dwika Putra, Erwin, Ermatita Ermatita, and Abdiansah Abdiansah. "Handwritten Kaganga script classification using deep learning and image fusion." Bulletin of Electrical Engineering and Informatics 14, no. 2 (2025): 1290–97. https://doi.org/10.11591/eei.v14i2.8747.

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Classification of traditional handwriting script and to preserve many cultures have been developed in some parts of the world, including image classification of handwriting Kaganga script. This study aims to propose a new combination model by implementing top-hat transform (THT) and contrast-limited adaptive histogram equalization (CLAHE) with discrete wavelet transform (DWT) to support the performance of the convolutional neural network (CNN) in Kaganga script classification. The top-hat transform and contrast-limited adaptive histogram equalization with discrete wavelet transform Fusion L2 c

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Firma, Aulia, and Sri Oktamuliani. "PENGOLAHAN FILTERING DAN CONTRAST ENHANCEMENT UNTUK MENINGKATKAN KUALITAS RESOLUSI CITRA ULTRASONOGRAFI ABDOMEN." JOURNAL ONLINE OF PHYSICS 8, no. 1 (2022): 51–54. http://dx.doi.org/10.22437/jop.v8i1.20607.

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Evaluasi penyaringan dan peningkatan kontras telah dilakukan untuk meningkatkan visualisasi gambar USG perut. Penelitian ini bertujuan untuk mengevaluasi hasil gabungan metode median filter dan filter Wiener menggunakan metode Histogram Equalization (HE), Contras Limited Adaptive Histogram Equalization (CLAHE), Contras Stretching (CS) secara kuantitatif menggunakan Mean Squared Error (MSE) dan Peak Signal-to-Noise Ratio (PSNR) dan kualitatif berdasarkan hasil wawancara dengan ahli radiologi. Data yang digunakan dalam penelitian ini adalah 30 data sekunder dari pasien USG abdomen. Penelitian di

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Juslan, Wulandari, and Alva Hendi Muhammad. "Evaluasi Kinerja Metode Peningkatan Kontras (CLAHE & HE) pada Klasifikasi Ras Kucing menggunakan VGG16." Edumatic: Jurnal Pendidikan Informatika 9, no. 1 (2025): 246–55. https://doi.org/10.29408/edumatic.v9i1.29578.

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Cat breed classification is challenging in image processing due to complex visual variations from crossbreeding, which affect care requirements. This study evaluates the effectiveness of Contrast Limited Adaptive Histogram Equalization (CLAHE) and Histogram Equalization (HE) in cat breed classification using a VGG16-based Convolutional Neural Network (CNN). The dataset consists of 4,656 cat images from six breeds, processed with CLAHE and HE for contrast enhancement before training. It is divided into 70% for training, 15% for validation, and 15% for testing. The model is trained for 10 epochs

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Alagulskhmi, A. "IMAGE RECOGNITION AND IDENTIFICATION USING MACHINE LEARNING." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 07, no. 12 (2023): 1–9. http://dx.doi.org/10.55041/ijsrem27729.

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Face recognition has been a rapidly growing and intriguing region progressively applications. A huge number of face recognition calculation have been produced in a long time ago. In this paper, for face detection we are using HOG (Histogram of oriented Gradient) based face detector which gives more accurate results rather than other machine learning algorithms like Haar Cascade. In recognition process we are using CLAHE (Contrast Limited Adaptive Histogram equalization) for pre-processing than we are using HOG which is a standard technique for features extraction. HOG features are extracted fo

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Román, Julio César Mello, Vicente R. Fretes, Carlos G. Adorno, et al. "Panoramic Dental Radiography Image Enhancement Using Multiscale Mathematical Morphology." Sensors 21, no. 9 (2021): 3110. http://dx.doi.org/10.3390/s21093110.

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Panoramic dental radiography is one of the most used images of the different dental specialties. This radiography provides information about the anatomical structures of the teeth. The correct evaluation of these radiographs is associated with a good quality of the image obtained. In this study, 598 patients were consecutively selected to undergo dental panoramic radiography at the Department of Radiology of the Faculty of Dentistry, Universidad Nacional de Asunción. Contrast enhancement techniques are used to enhance the visual quality of panoramic dental radiographs. Specifically, this artic

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Kurniawan, Muhammad Bayu, and Ema Utami. "COMPARATIVE ANALYSIS OF CONTRAST ENHANCEMENT METHODS FOR CLASSIFICATION OF PEKALONGAN BATIK MOTIFS USING CONVOLUTIONAL NEURAL NETWORK." Jurnal Teknik Informatika (Jutif) 5, no. 6 (2024): 1779–87. https://doi.org/10.52436/1.jutif.2024.5.6.2621.

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Batik artists in Pekalongan have freedom in determining motifs, creating a diversity of distinctive batik motifs. However, this diversity often makes it difficult for people to recognize the different motifs, as visual identification requires in-depth knowledge. The lack of understanding about Pekalongan batik is a challenge in recognizing these motifs. To overcome this challenge, an efficient and accurate method of motif identification is needed. This study aims to analyze the efficacy of contrast enhancement methods in improving the classification results of Pekalongan batik motifs using con

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Ma, Jinxiang, Xinnan Fan, Simon X. Yang, Xuewu Zhang, and Xifang Zhu. "Contrast Limited Adaptive Histogram Equalization-Based Fusion in YIQ and HSI Color Spaces for Underwater Image Enhancement." International Journal of Pattern Recognition and Artificial Intelligence 32, no. 07 (2018): 1854018. http://dx.doi.org/10.1142/s0218001418540186.

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To improve contrast and restore color for underwater images without suffering from insufficient details and color cast, this paper proposes a fusion algorithm for different color spaces based on contrast limited adaptive histogram equalization (CLAHE). The original color image is first converted from RGB space to two different spaces: YIQ and HSI. Then, the algorithm separately applies CLAHE in YIQ and HSI color spaces to obtain two different enhanced images. After that, the YIQ and HSI enhanced images are respectively converted back to RGB space. When the three components of red, green, and b

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Mahesh, Manik Kumbhar, and B. Godbole Bhalchandra. "Dehazing Effects on Image and Videousing AHE, CLAHE and Dark Channel Prior." International Journal of Engineering and Advanced Technology (IJEAT) 9, no. 3 (2020): 119–25. https://doi.org/10.35940/ijeat.C4833.029320.

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The image captured by camera is degraded by various atmospheric parameters for example rain, storm, wind, haze, snow. The removing haze is called dehazing, is naturally done in the physical degradation model that requires a resolution of an ill-posed inverse problem. In this paper discussion and e relative study of Adaptive Histogram Equalization (AHE) as well as Contrast limited adaptive histogram equalization (CLAHE) and dark channel prior (DCP). This article suggest image and video dehazing technique working on DCP method. The DCP is resulted from the characteristics of images taken in outd

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Nikhil Raje. "Hybrid DL Models for Improved Accuracy in Diagnosing Chronic Obstructive Pulmonary Disease." Advances in Nonlinear Variational Inequalities 27, no. 4 (2024): 385–91. http://dx.doi.org/10.52783/anvi.v27.1605.

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Chronic Obstructive Pulmonary Disease (COPD) is a common respiratory disorder marked by enduring airflow obstruction, leading to considerable illness and death rates. Timely and precise diagnosis is essential for proper management and treatment. In this study, we present a novel hybrid deep learning (DL) model leveraging an Autoencoder-GAN (Generative Adversarial Network) architecture to improve the accuracy of COPD diagnosis. Our approach incorporates a cutting-edge preprocessing method, Adaptive Histogram Equalization with Contrast Limited Adaptive Histogram Equalization (CLAHE), to enhance

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Liu, Chengwei, Xiubao Sui, Xiaodong Kuang, Yuan Liu, Guohua Gu, and Qian Chen. "Adaptive Contrast Enhancement for Infrared Images Based on the Neighborhood Conditional Histogram." Remote Sensing 11, no. 11 (2019): 1381. http://dx.doi.org/10.3390/rs11111381.

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In this paper, an adaptive contrast enhancement method based on the neighborhood conditional histogram is proposed to improve the visual quality of thermal infrared images. Existing block-based local contrast enhancement methods usually suffer from the over-enhancement of smooth regions or the loss of some details. To address these drawbacks, we first introduce a neighborhood conditional histogram to adaptively enhance the contrast and avoid the over-enhancement caused by the original histogram. Then the clip-redistributed histogram of the contrast-limited adaptive histogram equalization (CLAH

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Attia, Salim J. "Assessment of Some Enhancement Methods of Renal X-ray Image." NeuroQuantology 18, no. 12 (2020): 01–05. http://dx.doi.org/10.14704/nq.2020.18.12.nq20231.

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The study focuses on assessment of the quality of some image enhancement methods which were implemented on renal X-ray images. The enhancement methods included Imadjust, Histogram Equalization (HE) and Contrast Limited Adaptive Histogram Equalization (CLAHE). The images qualities were calculated to compare input images with output images from these three enhancement techniques. An eight renal x-ray images are collected to perform these methods. Generally, the x-ray images are lack of contrast and low in radiation dosage. This lack of image quality can be amended by enhancement process. Three q

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A., Manjunath, Neelappa Neelappa, Prakash Prakash, Veeramma Yatnalli, and Saroja S. Bhusare. "Performance Analysis of Graph theory-based Contrast Limited Adaptive Histogram Equalization for Image Enhancement." WSEAS TRANSACTIONS ON SYSTEMS 22 (March 9, 2023): 219–30. http://dx.doi.org/10.37394/23202.2023.22.23.

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Nowadays, image enhancement has become a major area of research because of the development of applications that are based on vision.Several digital image processing systems employ such image enhancement strategies with the help of graph theory. As the visibility level in low contrast image features is very less,several image enhancement strategies have been introduced with spatial transformations to enhance image qualityfor improved visualization. Nowadays, image processing plays an important role in the analysis of a patient’s health status and has become extremely popular in medical areas fo

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S. Magar, Satyawati, and Bhavani Sridharan. "Optimization Before Biomedical Image Compression Using CLAHE and DCS." International Journal of Engineering & Technology 7, no. 3.27 (2018): 236. http://dx.doi.org/10.14419/ijet.v7i3.27.17884.

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In current years, improving the Compression Ratio (CR) in medical imaging is essential and becomes big challenge in the field of biomedical. In that direction we have done optimization before biomedical image compression. For the same we have used the image enhancement techniques. For the enhancement of an image we have used Contrast Limited Adaptive Histogram Equalization (CLAHE) and Decorrelation Stretch (DCS) algorithms. By optimizing an image before compression we have achieved better Compression Ratio (CR) and Peak Signal to Noise Ratio (PSNR) than existing methods of an image compression

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Sree Vidya, B., and E. Chandra. "Triangular Fuzzy Membership-Contrast Limited Adaptive Histogram Equalization (TFM-CLAHE) for Enhancement of Multimodal Biometric Images." Wireless Personal Communications 106, no. 2 (2019): 651–80. http://dx.doi.org/10.1007/s11277-019-06184-6.

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Mapayi, Temitope, Serestina Viriri, and Jules-Raymond Tapamo. "Comparative Study of Retinal Vessel Segmentation Based on Global Thresholding Techniques." Computational and Mathematical Methods in Medicine 2015 (2015): 1–15. http://dx.doi.org/10.1155/2015/895267.

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Due to noise from uneven contrast and illumination during acquisition process of retinal fundus images, the use of efficient preprocessing techniques is highly desirable to produce good retinal vessel segmentation results. This paper develops and compares the performance of different vessel segmentation techniques based on global thresholding using phase congruency and contrast limited adaptive histogram equalization (CLAHE) for the preprocessing of the retinal images. The results obtained show that the combination of preprocessing technique, global thresholding, and postprocessing techniques

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Anifah, Lilik, I. Ketut Eddy Purnama, Mochamad Hariadi, and Mauridhi Hery Purnomo. "Osteoarthritis Classification Using Self Organizing Map Based on Gabor Kernel and Contrast-Limited Adaptive Histogram Equalization." Open Biomedical Engineering Journal 7, no. 1 (2013): 18–28. http://dx.doi.org/10.2174/1874120701307010018.

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Localization is the first step in osteoarthritis (OA) classification. Manual classification, however, is time-consuming, tedious, and expensive. The proposed system is designed as decision support system for medical doctors to classify the severity of knee OA. A method has been proposed here to localize a joint space area for OA and then classify it in 4 steps to classify OA into KL-Grade 0, KL-Grade 1, KL-Grade 2, KL-Grade 3 and KL-Grade 4, which are preprocessing, segmentation, feature extraction, and classification. In this proposed system, right and left knee detection was performed by emp

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Kryjak, Tomasz, Krzysztof Blachut, Hubert Szolc, and Mateusz Wasala. "Real-Time CLAHE Algorithm Implementation in SoC FPGA Device for 4K UHD Video Stream." Electronics 11, no. 14 (2022): 2248. http://dx.doi.org/10.3390/electronics11142248.

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One of the problems encountered in the field of computer vision and video data analysis is the extraction of information from low-contrast images. This problem can be addressed in several ways, including the use of histogram equalisation algorithms. In this work, a method designed for this purpose—the Contrast-Limited Adaptive Histogram Equalization (CLAHE) algorithm—is implemented in hardware. An FPGA platform is used for this purpose due to the ability to run parallel computations and very low power consumption. To enable the processing of a 4K resolution (UHD, 3840 × 2160 pixels) video stre

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Raharjo, Ahmad Solikhin Gayuh, and Endang Sugiharti. "Alphabet Classification of Sign System Using Convolutional Neural Network with Contrast Limited Adaptive Histogram Equalization and Canny Edge Detection." Scientific Journal of Informatics 10, no. 3 (2023): 239–50. http://dx.doi.org/10.15294/sji.v10i3.44137.

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Purpose: There are deaf people who have problems in communicating orally because they do not have the ability to speak and hear. The sign system is used as a solution to this problem, but not everyone understands the use and meaning of the sign system, even in terms of the alphabet. Therefore, it is necessary to classify a sign system in the form of American Sign Language (ASL) using Artificial Intelligence technology to get good results.Methods: This research focuses on improving the accuracy of ASL alphabet classification using the VGG-19 and ResNet50 architecture of the Convolutional Neural

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Vrochidis, Alexandros, Dimitrios Tzovaras, and Stelios Krinidis. "Enhancing 3D Reconstructions in Underwater Environments: The Impact of Image Enhancement on Model Quality." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLVIII-2/W10-2025 (July 7, 2025): 317–24. https://doi.org/10.5194/isprs-archives-xlviii-2-w10-2025-317-2025.

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Abstract. 3D reconstructions in underwater environments face significant challenges due to poor image quality, caused by blurring, reduced contrast, color distortion, and inadequate lighting. This study investigates the impact of various image enhancement techniques on underwater 3D reconstruction, focusing on Contrast Limited Adaptive Histogram Equalization (CLAHE), RGB Histogram Stretching (RGHS), and a combined approach integrating RGB stretching with CLAHE. Three real-world underwater datasets were analyzed to assess the effectiveness of these methods in improving the accuracy and complete

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