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Journal articles on the topic 'Contrast Limited Histogram Equalization'

Author: Grafiati

Published: 3 June 2025

Last updated: 31 July 2025

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1

Stimper, Vincent, Stefan Bauer, Ralph Ernstorfer, Bernhard Scholkopf, and Rui Patrick Xian. "Multidimensional Contrast Limited Adaptive Histogram Equalization." IEEE Access 7 (2019): 165437–47. http://dx.doi.org/10.1109/access.2019.2952899.

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2

Kanika, Kapoor, and Arora Shaveta. "COLOUR IMAGE ENHANCEMENT BASED ON HISTOGRAM EQUALIZATION." Electrical & Computer Engineering: An International Journal (ECIJ) 4, no. 3 (2015): 73–82. https://doi.org/10.5281/zenodo.3593819.

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Histogram equalization is a nonlinear technique for adjusting the contrast of an image using its histogram. It increases the brightness of a gray scale image which is different from the mean brightness of the original image. There are various types of Histogram equalization techniques like Histogram Equalization, Contrast Limited Adaptive Histogram Equalization, Brightness Preserving Bi Histogram Equalization, Dualistic Sub Image Histogram Equalization, Minimum Mean Brightness Error Bi Histogram Equalization, Recursive Mean Separate Histogram Equalization and Recursive Sub Image Histogram Equa

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3

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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Fan, Xin, Junyan Wang, Haifeng Wang, and Changgao Xia. "Contrast-Controllable Image Enhancement Based on Limited Histogram." Electronics 11, no. 22 (2022): 3822. http://dx.doi.org/10.3390/electronics11223822.

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To address the technical shortcomings of conventional histogram equalization (HE), such as over-enhancement and artifacts, we propose a histogram-constrained and contrast-tunable HE technique for digital image enhancement. Firstly, the input image histogram is partitioned into two parts, the main histogram and the constrained histogram, by a cumulative probability density threshold; second, the main histogram is redistributed equally in the whole grayscale range; and finally, the nonlinearity of the constrained histogram is mapped to the main histogram. The experimental averages show that the

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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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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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Nurhidayah, Bannu Abdul Samad, and Bualkar Abdullah. "Perbandingan Metode Contrast Enhancement pada Citra CT-Scan Kanker Paru-paru." Gravitasi 19, no. 2 (2020): 24–28. http://dx.doi.org/10.22487/gravitasi.v19i2.15360.

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Abstrak: Di Indonesia kanker paru menjadi penyebab kematian kedua setelah kanker payudara. Angka mortalitas yang cukup tinggi, maka penentuan diagnosis lebih awal memegang peranan yang sangat penting dalam manajemen terapi. Kelemahan CT-Scan dalam mendiagnosa kanker paru-paru disebabkan oleh kontras citra yang rendah dan derau pada citra. Pada penelitian ini akan membandingkan metode contrast enhancement berbasis histogram equalization dan contrast limited adaptive histogram equalization untuk meningkatkan kualitas citra dengan menggunakan software Matlab. Namun, sebelumnya dilakukan red

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Zuo, Chao, Qian Chen, and Xiubao Sui. "Range Limited Bi-Histogram Equalization for image contrast enhancement." Optik 124, no. 5 (2013): 425–31. http://dx.doi.org/10.1016/j.ijleo.2011.12.057.

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Lawton, Sahil, and Serestina Viriri. "Detection of COVID-19 from CT Lung Scans Using Transfer Learning." Computational Intelligence and Neuroscience 2021 (April 8, 2021): 1–14. http://dx.doi.org/10.1155/2021/5527923.

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This paper aims to investigate the use of transfer learning architectures in the detection of COVID-19 from CT lung scans. The study evaluates the performances of various transfer learning architectures, as well as the effects of the standard Histogram Equalization and Contrast Limited Adaptive Histogram Equalization. The findings of this study suggest that transfer learning-based frameworks are an alternative to the contemporary methods used to detect the presence of the virus in patients. The highest performing model, the VGG-19 implemented with the Contrast Limited Adaptive Histogram Equali

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10

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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Rudikov, S. I., V. Yu Tsviatkou, and A. P. Shkadarevich. "Dynamic range reduction of infrared images based on adaptive equalization, stretch and compression of histogram." Proceedings of the National Academy of Sciences of Belarus, Physical-Technical Series 66, no. 4 (2021): 470–82. http://dx.doi.org/10.29235/1561-8358-2021-66-4-470-482.

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The problem of reducing the dynamic range and improving the quality of infrared (IR) images with a wide dynamic range for their display on a liquid crystal matrix with 8-bit pixels is considered. To solve this problem in optoelectronic devices in real time, block algorithms based on local equalization of the histogram are widely used, taking into account their relatively low computational complexity and the possibility of taking into account local features of the brightness distribution. The basic adaptive histogram equalization algorithm provides reasonably high image quality after conversion

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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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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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Pandey, Kanchan, Sapna Singh, and Rachana Mishra. "Range Limited Quad-Histogram Equalization Method for Image Contrast Enhancement." International Journal of Computer Applications 91, no. 15 (2014): 14–20. http://dx.doi.org/10.5120/15956-5316.

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15

Agarwal, Monika, and Rashima Mahajan. "Medical Image Contrast Enhancement using Range Limited Weighted Histogram Equalization." Procedia Computer Science 125 (2018): 149–56. http://dx.doi.org/10.1016/j.procs.2017.12.021.

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16

Chang, Yakun, Cheolkon Jung, Peng Ke, Hyoseob Song, and Jungmee Hwang. "Automatic Contrast-Limited Adaptive Histogram Equalization With Dual Gamma Correction." IEEE Access 6 (2018): 11782–92. http://dx.doi.org/10.1109/access.2018.2797872.

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Faek, Fatma, Omaima Nomir, Ehab Essa, and Ebrahim El-henawy. "Wavelet-based Video Enhancement Using Contrast Limited Adaptive Histogram Equalization." Mansoura Journal for Computer and Information Sciences 14, no. 1 (2018): 43–52. http://dx.doi.org/10.21608/mjcis.2018.311997.

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18

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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19

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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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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21

Yu, Cheng-Yi, Hsueh-Yi Lin, and Tzu-Wei Yu. "Modulated AIHT Image Contrast Enhancement Algorithm based on Contrast-Limited Adaptive Histogram Equalization." Applied Mathematics & Information Sciences 7, no. 2L (2013): 449–54. http://dx.doi.org/10.12785/amis/072l10.

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22

Xu, Honglie, Qian Chen, Chao Zuo, Chunhua Yang, and Ning Liu. "Range limited double-thresholds multi-histogram equalization for image contrast enhancement." Optical Review 22, no. 2 (2015): 246–55. http://dx.doi.org/10.1007/s10043-015-0073-x.

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23

Zhou, Shangbo, Fuping Zhang, and Muhammad Abubakar Siddique. "Range Limited Peak-Separate Fuzzy Histogram Equalization for image contrast enhancement." Multimedia Tools and Applications 74, no. 17 (2014): 6827–47. http://dx.doi.org/10.1007/s11042-014-1931-4.

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24

Magudeeswaran, V., and J. Fenshia Singh. "Contrast limited fuzzy adaptive histogram equalization for enhancement of brain images." International Journal of Imaging Systems and Technology 27, no. 1 (2017): 98–103. http://dx.doi.org/10.1002/ima.22214.

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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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B Shoba Rani. "Modified Effective Histogram Equalization method for Night Time Color image enhancement with Energy Curve." Journal of Information Systems Engineering and Management 10, no. 49s (2025): 873–83. https://doi.org/10.52783/jisem.v10i49s.10001.

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By modifying brightness, contrast, sharpness, and color balance, color photographs can be made more visually appealing. By highlighting significant characteristics and reducing noise or distortion, the main aim of enhancement is to make the image more aesthetically visible, lucid, and interpretable. Techniques vary from basic brightness and contrast tweaks to sophisticated algorithms. Improved quality in low-light video is vital for distinguishing individuals and activities in security and surveillance. Challenges like noise amplification and over-enhancement can create unnatural images with e

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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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Dong, Wei, Maikon Nascimento, and Dileepan Joseph. "Model-Based Design of Contrast-Limited Histogram Equalization for Low-Complexity, High-Speed, and Low-Power Tone-Mapping Operation." Electronics 14, no. 12 (2025): 2416. https://doi.org/10.3390/electronics14122416.

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Imaging applications involving outdoor scenes and fast motion require sensing and processing of high-dynamic-range images at video rates. In turn, image signal processing pipelines that serve low-dynamic-range displays require tone mapping operators (TMOs). For high-speed and low-power applications with low-cost field-programmable gate arrays (FPGAs), global TMOs that employ contrast-limited histogram equalization prove ideal. To develop such TMOs, this work proposes a MATLAB–Simulink–Vivado design flow. A realized design capable of megapixel video rates using milliwatts of power requires only

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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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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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31

Völgyes, David, Anne Martinsen, Arne Stray-Pedersen, Dag Waaler, and Marius Pedersen. "A Weighted Histogram-Based Tone Mapping Algorithm for CT Images." Algorithms 11, no. 8 (2018): 111. http://dx.doi.org/10.3390/a11080111.

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Computed Tomography (CT) images have a high dynamic range, which makes visualization challenging. Histogram equalization methods either use spatially invariant weights or limited kernel size due to the complexity of pairwise contribution calculation. We present a weighted histogram equalization-based tone mapping algorithm which utilizes Fast Fourier Transform for distance-dependent contribution calculation and distance-based weights. The weights follow power-law without distance-based cut-off. The resulting images have good local contrast without noticeable artefacts. The results are compared

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Baek, Jiyeon, Yejin Kim, Byungjin Chung, and Changhoon Yim. "Linear Spectral Clustering with Contrast-limited Adaptive Histogram Equalization for Superpixel Segmentation." IEIE Transactions on Smart Processing & Computing 8, no. 4 (2019): 255–64. http://dx.doi.org/10.5573/ieiespc.2019.8.4.255.

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Suharyanto, Z. A. Hasibuan, P. N. Andono, D. Pujiono, and R. I. M. Setiadi. "Contrast Limited Adaptive Histogram Equalization for Underwater Image Matching Optimization use SURF." Journal of Physics: Conference Series 1803, no. 1 (2021): 012008. http://dx.doi.org/10.1088/1742-6596/1803/1/012008.

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A., Thamizharasi, and Jayasudha J.S. "AN ILLUMINATION INVARIANT FACE RECOGNITION BY ENHANCED CONTRAST LIMITED ADAPTIVE HISTOGRAM EQUALIZATION." ICTACT Journal on Image and Video Processing 06, no. 04 (2016): 1258–66. http://dx.doi.org/10.21917/ijivp.2016.0183.

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Min, Byong-Seok, and Tae-Kyung Cho. "A Novel Method of Determining Parameters for Contrast Limited Adaptive Histogram Equalization." Journal of the Korea Academia-Industrial cooperation Society 14, no. 3 (2013): 1378–87. http://dx.doi.org/10.5762/kais.2013.14.3.1378.

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gamal, Aya M., H. I. Ashiba, Ghada ElBanby, Adel S. Elfishawy, Nabil A. Ismail, and Fathi E. Abd El-Samie. "Infrared Video Enhancement Using Contrast Limited Adaptive Histogram Equalization and Fuzzy Logic." Menoufia Journal of Electronic Engineering Research 28, no. 1 (2019): 231–36. http://dx.doi.org/10.21608/mjeer.2019.77373.

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Sasi, Neethu M., and V. K. Jayasree. "Contrast Limited Adaptive Histogram Equalization for Qualitative Enhancement of Myocardial Perfusion Images." Engineering 05, no. 10 (2013): 326–31. http://dx.doi.org/10.4236/eng.2013.510b066.

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Singh, Prerna, Ramakrishnan Mukundan, and Rex De Ryke. "Feature Enhancement in Medical Ultrasound Videos Using Contrast-Limited Adaptive Histogram Equalization." Journal of Digital Imaging 33, no. 1 (2019): 273–85. http://dx.doi.org/10.1007/s10278-019-00211-5.

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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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Fu, Qingqing, Zhengbing Zhang, Mehmet Celenk, and Aiping Wu. "A POSHE-Based Optimum Clip-Limit Contrast Enhancement Method for Ultrasonic Logging Images." Sensors 18, no. 11 (2018): 3954. http://dx.doi.org/10.3390/s18113954.

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Enabled by piezoceramic transducers, ultrasonic logging images often suffer from low contrast and indistinct local details, which makes it difficult to analyze and interpret geologic features in the images. In this work, we propose a novel partially overlapped sub-block histogram-equalization (POSHE)-based optimum clip-limit contrast enhancement (POSHEOC) method to highlight the local details hidden in ultrasonic well logging images obtained through piezoceramic transducers. The proposed algorithm introduces the idea of contrast-limited enhancement to modify the cumulative distribution functio

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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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Harichandana, M., V. Sowmya, V. V. Sajithvariyar, and R. Sivanpillai. "COMPARISON OF IMAGE ENHANCEMENT TECHNIQUES FOR RAPID PROCESSING OF POST FLOOD IMAGES." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIV-M-2-2020 (November 17, 2020): 45–50. http://dx.doi.org/10.5194/isprs-archives-xliv-m-2-2020-45-2020.

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Abstract. Satellite images are widely used for assessing the areal extent of flooded areas. However, presence of clouds and shadow limit the utility of these images. Numerous digital algorithms are available for enhancing such images and highlighting areas of interest. These algorithms range from simple to complex, and the time required to process these images also varies considerably. For disaster response, it is important to select an algorithm that can enhance the quality of the images in relatively short time. This study compared the relative performance of five traditional (Histogram Equa

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Liu, Peng, Xingquan Zhao, Xuchong Wang, et al. "A Multi-Stage Enhancement Based on the Attenuation Characteristics of X-Band Marine Radar Images for Oil Spill Extraction." Oceans 6, no. 3 (2025): 39. https://doi.org/10.3390/oceans6030039.

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Marine oil spills cause significant environmental damage worldwide. Marine radar imagery is used for oil spill detection. However, the rapid attenuation of backscatter intensity with increasing distance limits detectable coverage. A multi-stage image enhancement framework integrating background clutter fitting subtraction, Multi-Scale Retinex, and Gamma correction is proposed. Experimental results using marine radar images sampled in the oil spill incident in Dalian 2010 are used to demonstrate the significant improvements. Compared to Contrast-Limited Adaptive Histogram Equalization and Parti

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Riadi, Aditya Akbar, Ahmad Abdul Chamid, and Akh Sokhibi. "ANALISIS KOMPARASI METODE PERBAIKAN KONTRAS BERBASIS HISTOGRAM EQUALIZATION PADA CITRA MEDIS." Simetris: Jurnal Teknik Mesin, Elektro dan Ilmu Komputer 8, no. 1 (2017): 383–88. http://dx.doi.org/10.24176/simet.v8i1.1026.

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Citra merupakan gambaran tentang karakteristik suatu obyek menurut kondisi variabel tertentu. Pengolahan citra bertujuan memperbaiki kualitas citra agar mudah diinterpretasi oleh manusia atau mesin (dalam hal ini komputer). Terdapat beberapa operasi di dalam pengolahan citra, salah satunya adalah perbaikan kontras yang pada dasarnya biasa digunakan untuk memunculkan bagian-bagian yang tidak terlihat (hidden feature) pada citra. Hasil citra dari rontgen yang tidak selalu memiliki kualitas citra yang baik, seperti halnya hasil citra x-ray yang terlalu gelap atau ada bagian tulang yang terlihat s

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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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Ulutas, Guzin, and Beste Ustubioglu. "Underwater image enhancement using contrast limited adaptive histogram equalization and layered difference representation." Multimedia Tools and Applications 80, no. 10 (2021): 15067–91. http://dx.doi.org/10.1007/s11042-020-10426-2.

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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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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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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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Mat Raffei, Anis Farihan, Hishammuddin Asmuni, Rohayanti Hassan, and Razib M. Othman. "A low lighting or contrast ratio visible iris recognition using iso-contrast limited adaptive histogram equalization." Knowledge-Based Systems 74 (January 2015): 40–48. http://dx.doi.org/10.1016/j.knosys.2014.11.002.

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