Relevant bibliographies by topics / CLAHE technique

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'CLAHE technique'

Author: Grafiati
Published: 5 June 2025
Last updated: 15 July 2025

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Journal articles on the topic "CLAHE technique"

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B. N, Madhukar. "Image Enhancement using CLAHE-DWT Technique." International Journal for Research in Applied Science and Engineering Technology 6, no. 5 (2018): 2076–81. http://dx.doi.org/10.22214/ijraset.2018.5340.

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DZULKIFLI, FAHMI AKMAL. "Identification of Suitable Contrast Enhancement Technique for Improving the Quality of Astrocytoma Histopathological Images." ELCVIA Electronic Letters on Computer Vision and Image Analysis 20, no. 1 (2021): 84–98. http://dx.doi.org/10.5565/rev/elcvia.1256.

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Contrast enhancement plays an important part in image processing. In histology, the application of a contrast enhancement technique is necessary since it can help pathologists in diagnosing the sample slides by increasing the visibility of the morphological and features of cells in an image. Various techniques have been proposed to enhance the contrast of microscopic images. Thus, this paper aimed to study the effectiveness of contrast enhancement techniques in enhancing the Ki67 images of astrocytoma. Three contrast enhancement techniques consist of contrast stretching, histogram equalization, and CLAHE techniques were proposed to enhance the sample images. The performance of each technique was compared by computing seven quantitative measures. The CLAHE technique was preferred for enhancing the contrast of the astrocytoma images. This technique produces good results especially in contrast enhancement, edge conservation and enhancement, brightness preservation, and minimum distortions to the enhanced images.
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Naser, Ahmed. "A proposed CLCOA Technique Based on CLAHE using Cat Optimized Algorithm for Plants Images Enhancement." Wasit Journal of Computer and Mathematics Science 3, no. 1 (2024): 18–27. http://dx.doi.org/10.31185/wjcms.202.

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Image Enhancement is one of the mainly significant with complex techniques in image study. The purpose of image enhancement is to advance the optical presence of an image, or to support a “improved convert representation for future mechanized image processing. Various images similar medical images, satellite images, natural with even real life photographs which have a lowly contrast and noise. This study presents a new enhancement technique based on standard contrast limited adaptive histogram equalization (CLAHE) technique for image enhancement which its name CLCOA. The suggested technique depends on augmentation of swarm intelligence via using Cat Swarm Optimization algorithm (CSO). The swarm intelligence is used to obtain the optimal structure of CLAHE technique. Tomato plant images have used and applied as dataset because of its important and influence in our life. For fair analysis of two techniques, Absolute Mean Brightness Error (AMBE), peak signal-to-noise ratio (PSNR), entropy and Contrast Gain of fundus images are analyzed by using MATLAB. The results show that performance of the proposed technique reveals the efficiently and robustness when compared results of standard technique.
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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 processing technique. The findings revealed that CLAHE markedly outperforms the other methods, offering superior contrast enhancement and detailed visibility. This suggests that CLAHE is the most proficient technique for augmenting new crescent moon visibility, thereby providing critical insights for future astronomical observations and practical applications. The research significantly advances the refinement of new crescent moon observation techniques, contributing to both scientific understanding and the enhancement of practical implementation in the field.
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Yakno, Marlina, Junita Mohamad-Saleh, and Mohd Zamri Ibrahim. "Dorsal Hand Vein Image Enhancement Using Fusion of CLAHE and Fuzzy Adaptive Gamma." Sensors 21, no. 19 (2021): 6445. http://dx.doi.org/10.3390/s21196445.

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Enhancement of captured hand vein images is essential for a number of purposes, such as accurate biometric identification and ease of medical intravenous access. This paper presents an improved hand vein image enhancement technique based on weighted average fusion of contrast limited adaptive histogram equalization (CLAHE) and fuzzy adaptive gamma (FAG). The proposed technique is applied using three stages. Firstly, grey level intensities with CLAHE are locally applied to image pixels for contrast enhancement. Secondly, the grey level intensities are then globally transformed into membership planes and modified with FAG operator for the same purposes. Finally, the resultant images from CLAHE and FAG are fused using improved weighted averaging methods for clearer vein patterns. Then, matched filter with first-order derivative Gaussian (MF-FODG) is employed to segment vein patterns. The proposed technique was tested on self-acquired dorsal hand vein images as well as images from the SUAS databases. The performance of the proposed technique is compared with various other image enhancement techniques based on mean square error (MSE), peak signal-to-noise ratio (PSNR), and structural similarity index measurement (SSIM). The proposed enhancement technique’s impact on the segmentation process has also been evaluated using sensitivity, accuracy, and dice coefficient. The experimental results show that the proposed enhancement technique can significantly enhance the hand vein patterns and improve the detection of dorsal hand veins.
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Momoh, Muyideen Omuya. "LWT-CLAHE Based Color Image Enhancement Technique: An Improved Design." Computer Engineering and Applications Journal 9, no. 2 (2020): 117–26. http://dx.doi.org/10.18495/comengapp.v9i2.329.

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Color image enhancement is one of important process and actually a vital precursory stage to other stages in the field of digital image processing. This is due to the fact that the effectiveness of processes in this stage on the output determines the success of other stages for a quality overall performance. This paper presents a color image enhancement technique using lifting wavelet transform (LWT) and contrast limited adaptive histogram equalization (CLAHE) to overcome the issue of noise amplification, over and under-enhancement in exiting enhancement techniques. Test images from Computer Vision Database were used for the proposed technique and the performance was evaluated using PSNR and SSIM. Result obtained shows an average improvement of 56.4% and 20.98% in terms of PSNR and SSIM respectively.
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Bhargavi, S., B. Sadhvik Reddy, T. Sumanth Reddy, T. Sushma, S. Narendra Reddy, and P. Sai Kusuma. "Detection of Illegal Goods using X-ray Image Enhancement Algorithm." International Journal for Research in Applied Science and Engineering Technology 12, no. 4 (2024): 1522–32. http://dx.doi.org/10.22214/ijraset.2024.60081.

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bstract: An X-ray image enhancement technique integrating USM+CLAHE+HAZEREMOVAL and YOLOV2 for object detection is presented to address the problem of colour distortion in CLAHE enhanced airport security X-ray images. Calculating the grayscale images on the R, G, and B channels of the X-ray image and applying CLAHE enhancement to each, then merging the enhanced R, G, and B grayscale images will take place. After that, USM sharpening operation is applied to the CLAHE-enhanced X-ray image, and then it is merged with the original and USM-sharpened images according to the weight. Later haze removal technique is added to obtained results. For detection, YOLOV2 is used. The results of the experiments reveal that the USM+CLAHE+ HAZEREMOVAL algorithm can successfully improve the security X-ray image while also suppressing colour distortion in the enhanced image
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Madhavi V., Vijaya, and P. Lalitha Surya Kumari. "A Qualitative Approach for Enhancing Fundus Images with Novel CLAHE Methods." Engineering, Technology & Applied Science Research 15, no. 1 (2025): 20102–7. https://doi.org/10.48084/etasr.9525.

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Glaucoma is a progressive eye disease. This study presents a custom technique to enhance retinal fundus images to detect glaucoma. Contrast enhancement is a crucial stage in medical image analysis to improve the visual impression of diseases. CLAHE is a common technique to improve images. Clip Limit (CL) and subimages may restrict the potential benefits of the typical approach and pose difficulties. This study introduces Enhanced CLAHE and Automated CLAHE to address the shortcomings of the base method. These methods demonstrate progress in improving retinal landmarks in various ways by looking directly at the in-depth description of retinal images. The proposed methods, along with the baseline CLAHE, were compared using quality assessment tools such as the Peak-Signal-to-Noise Ratio (PSNR). The results help to determine the degree of contrast enhancement and the overall richness of the image.
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Khozaimi, Ach, Isnani Darti, Syaiful Anam, and Wuryansari Muharini Kusumawinahyu. "Advanced cervical cancer classification: enhancing pap smear images with hybrid PMD filter-CLAHE." Indonesian Journal of Electrical Engineering and Computer Science 39, no. 1 (2025): 644. https://doi.org/10.11591/ijeecs.v39.i1.pp644-655.

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Cervical cancer remains a significant health problem, especially in developing countries. Early detection is critical for effective treatment. Convolutional neural networks (CNN) have shown promise in automated cervical cancer screening, but their performance depends on pap smear image quality. This study investigates the impact of various image preprocessing techniques on CNN performance for cervical cancer classification using the SIPaKMeD dataset. Three preprocessing techniques were evaluated: PeronaMalik diffusion (PMD) filter for noise reduction, contrast-limited adaptive histogram equalization (CLAHE) for image contrast enhancement, and the proposed hybrid PMD filter-CLAHE approach. The enhanced image datasets were evaluated on pretrained models, such as ResNet-34, ResNet-50, SqueezeNet-1.0, MobileNet-V2, EfficientNet-B0, EfficientNet-B1, DenseNet121, and DenseNet-201. The results show that hybrid preprocessing PMD filter-CLAHE can improve the pap smear image quality and CNN architecture performance compared to the original images. The maximum metric improvements are 13.62% for accuracy, 10.04% for precision, 13.08% for recall, and 14.34% for F1-score. The proposed hybrid PMD filter-CLAHE technique offers a new perspective in improving cervical cancer classification performance using CNN architectures.
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Hashmi, Adeel, Abhinav Juneja, Naresh Kumar, et al. "Contrast Enhancement in Mammograms Using Convolution Neural Networks for Edge Computing Systems." Scientific Programming 2022 (April 11, 2022): 1–9. http://dx.doi.org/10.1155/2022/1882464.

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A good contrast is significant for analysis of medical images, and if the images have poor contrast, then some methods of contrast enhancement can be of much benefit. In this paper, a convolution neural network-based transfer learning approach is utilized for contrast enhancement of mammographic images. The experiments are conducted on ISP and MIAS datasets, where ISP dataset is used for training and MIAS dataset is used for testing (contrast enhancement). Experimental comparison of the proposed technique is done with the most popular direct and indirect contrast enhancement techniques such as CLAHE, BBHE, RMSHE, and contrast stretching. A qualitative comparison is done using mean square error (MSE), signal to noise ratio (SNR), and peak signal to noise ratio (PSNR). It is observed that the proposed technique outperforms the other techniques HE, RMSHE, CLAHE, BBHE, and contrast stretching.
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Dissertations / Theses on the topic "CLAHE technique"

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Percy, Heather Louise. ""Giving New Life to Old Ideas": the synthesis of Early Music Techniques with modern practice in the music of Judith Bingham, Clare Maclean and Heather Percy." Thesis, The University of Sydney, 2022. https://hdl.handle.net/2123/29717.

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The appropriation of compositional techniques from earlier musical styles within contemporary composition is a practice that composers have been adopting for centuries. Indeed, Arvo Pärt, one of the most influential contemporary composers of sacred music, developed his unique sound world by employing old composition techniques. This thesis is concerned with the re-interpretation of early music composition techniques within contemporary sacred choral music. It focuses specifically on the music of female composers Judith Bingham (United Kingdom) and Clare Maclean (Australia/New Zealand), exploring the role that early music techniques play within their composition style and aesthetic, and provides a route to ways that I may incorporate similar elements in my own work. Approaches to ancient techniques are examined in the following works by Bingham and Maclean: Epiphany (1996) and Sanctus and “Lamb of God” from Missa Brevis Awake My Soul (2007) by Bingham and Maclean’s Sanctus and Agnus Dei from Osanna Mass (2008). As well as identifying early music composition techniques, I explore the sound-worlds of both composers, recognising their contribution to advanced harmonic practice. These findings contribute towards an understanding of these composers’ stylistic trademarks and their individual musical aesthetics, which in turn have influenced my own creative work and are demonstrated in the accompanying portfolio of original compositions. This research confirms that contemporary composers continue to utilise ancient techniques as part of the creation of new music and that this practice can be further explored by emerging composers. It also brings to the fore the sacred choral music of Bingham and Maclean and documents their contribution towards the canon of contemporary sacred choral music in Australia and abroad.
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Books on the topic "CLAHE technique"

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D, Denison Cara, and Pierpont Morgan Library, eds. The Thaw collection: Master drawings and new acquisitions. Pierpont Morgan Library, 1994.

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Media, Irb. Summary of Clare Goodwin's Getting Pregnant with PCOS. IRB MEDIA, 2022.

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Media, I. R. B. Summary of Clare Connelly's Betrayed by the CEO. IRB Media, 2021.

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Goines, Lincoln, and Robby Ameen. Funkifying the Clave: Afro-Cuban Grooves for Bass and Drums (with CD) (Manhattan Music Publications). Warner Bros Pubns, 1993.

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PROGRAMA HARDCORE: Cómo Construir Hábitos y Rutinas de Clase Mundial. Estrategias Comprobadas para la Pérdida de Peso, el éxito y una Salud óptima. Cómo Convertirse en un Nuevo Yo a Través de la Optimización de Rituales y Rutinas. Dr. Ernesto Martinez, 2022.

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PROGRAMA HARDCORE: Cómo Construir Hábitos y Rutinas de Clase Mundial. Estrategias Comprobadas para la Pérdida de Peso, el éxito y una Salud óptima. Cómo Convertirse en un Nuevo Yo a Través de la Optimización de Rituales y Rutinas. Dr. Ernesto Martinez, 2022.

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PROGRAMA HARDCORE: Cómo Construir Hábitos y Rutinas de Clase Mundial. Estrategias Comprobadas para la Pérdida de Peso, el éxito y una Salud óptima. Cómo Convertirse en un Nuevo Yo a Través de la Optimización de Rituales y Rutinas. Dr. Ernesto Martinez, 2022.

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Guss-West, Clare. Attention and Focus in Dance. Human Kinetics, 2021. http://dx.doi.org/10.5040/9781718212718.

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The Western approach to dance is largely focused on control and mastery of technique, both of which are certainly necessary skills for improving performance. But mindful attention, despite its critical role in high performance, has gotten short shrift—until now. Attention and Focus in Dance, a how-to book rooted in the 20 years of attentional focus findings of researcher Gabriele Wulf, will help dancers unlock their power and stamina reserves, enabling efficient movement, heightening their sensory perception and releasing their dance potential. Author Clare Guss-West—a professional dancer, choreographer, teacher and holistic practitioner—presents a systematic, science-based approach to the mental work of dance. Her approach helps dancers hone the skills of attention, focus and self-cueing to replenish energy and enhance their physical and artistic performance. A Unique, Research-Based Approach Here is what Attention and Focus in Dance offers readers: • A unique approach, connecting the foundations of Eastern movement with Western movement forms • Research-based teaching practices in diverse contexts, including professional dance companies, private studios, and programmes for dancers with special needs or movement challenges • Testimonies and tips from international professional dancers and dance educators who use the book's approach in their training and teaching • A dance-centric focus that can be easily integrated into existing training and teaching practice, in rehearsal, or in rehabilitation contexts to provide immediate and long-term benefits Guss-West explores attentional focus techniques for dancers, teachers and dance health care practitioners, making practical connections between research, movement theory and day-to-day dance practice. “Many dancers are using excessive energy deployment and significant counterproductive effort, and that can lead to a global movement dysfunction, lack of stamina and an increased risk of injury,” says Guss-West. “Attentional focus training is the most relevant study that sport science and Eastern-movement practice can bring to dance.” Book Organisation The text is organised into two parts. Part I guides dancers in looking at the attentional challenges and information overload that many professional dancers suffer from. It outlines the need for a systematic attention and focus strategy, and it explains how scientific research on attentional focus relates to dance practice. This part also examines the ways in which Eastern-movement principles intersect with and complement scientific findings, and it examines how the Eastern and scientific concepts can breathe new life into basic dance elements such as posture, turnout and port de bras. Attention and focus techniques are included for replenishing energy and protecting against energy depletion and exhaustion. Part II presents attention and focus strategies for teaching, self-coaching and cueing. It addresses attentional focus cues for beginners and for more advanced dancers and professionals, and it places attentional focus in the broader context of holistic teaching strategies. Maximising Dance Potential “Whether cueing others or yourself, cueing for high performance is an art,” Guss-West says. “Readers will discover how to format cues and feedback to facilitate effective neuromuscular response and enhance dancer recall of information and accessibility while dancing.” Attention and Focus in Dance offers an abundance of research-backed concepts and inspirational ideas that can help dancers in their learning and performance. This book aids readers in filtering information and directing their focus for optimal physical effect. Ultimately, it guides dancers and teachers in being the best version of themselves and maximising their potential in dance.
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Wiles, Stephaanie, Peter Dreyer, and Evelyn J. Phimister. The Thaw Collection: Master Drawings and New Acquisitions. Pierpont Morgan Library, 1994.

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Book chapters on the topic "CLAHE technique"

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Raja Rajeswari Chandni, P., Judith Justin, and R. Vanithamani. "Fundus Image Enhancement Using EAL-CLAHE Technique." In Advances in Data and Information Sciences. Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-5689-7_54.

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Sathiya, L., and V. Palanisamy. "Minor Finger Knuckle Print Image Enhancement Using CLAHE Technique." In New Trends in Computational Vision and Bio-inspired Computing. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-41862-5_67.

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Ramon-Mateu, Julia, Allison Edgar, Dorothy Mitchell, and Mark Q. Martindale. "Studying Ctenophora WBR Using Mnemiopsis leidyi." In Methods in Molecular Biology. Springer US, 2022. http://dx.doi.org/10.1007/978-1-0716-2172-1_5.

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AbstractCtenophores, also known as comb jellies, are a clade of fragile holopelagic, carnivorous marine invertebrates, that represent one of the most ancient extant groups of multicellular animals. Ctenophores show a remarkable ability to regenerate in the adult form, being capable of replacing all body parts (i.e., whole-body regeneration) after loss/amputation. With many favorable experimental features (optical clarity, stereotyped cell lineage, multiple cell types), a full genome sequence available and their early branching phylogenetic position, ctenophores are well placed to provide information about the evolution of regenerative ability throughout the Metazoa. Here, we provide a collection of detailed protocols for use of the lobate ctenophore Mnemiopsis leidyi to study whole-body regeneration, including specimen collection, husbandry, surgical manipulation, and imaging techniques.
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Parsons, Sylvia K., Christine Erbe, Sarah A. Marley, and Miles J. Parsons. "Pinniped Sounds." In Marine Mammal Acoustics in a Noisy Ocean. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-77022-7_5.

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Abstract Pinnipeds are a highly vocal clade of semiaquatic marine mammals, producing sounds above and below water. They originate from 13 of the 18 International Union for Conservation of Nature (IUCN) global regions (exceptions being the Caribbean, Central Indian, Arabian, East African, and East Asian regions). Of 34 IUCN-listed extant species (plus subspecies), 32 species have reports of sound production in air and 22 under water. Like other marine fauna, their call characteristics and cue rates (i.e., the number of calls produced per unit of time) are often related to biological traits, learned and innate acoustic behavior, the associated life functions, and the physical environment in which sounds are produced, which can vary among species and families. For example, feeding occurs in the water, while rearing pups mostly occurs in air (i.e., on land or ice) for all species. In contrast, courtship, a highly vocal activity, is conducted primarily on land by Otariidae (eared seals) but mostly at sea by Phocidae (earless seals) and Odobenidae (walruses). The physical limitations of producing sound under water and the differences between propagation in water and air mean that call characteristics and ecology for sound production in these two media should be considered separately. Inter- and intraspecies variation is significant and not necessarily related to phylogeny. Some closely related species display vastly different repertoires, while distantly related species can be similar in complexity and repertoire size, highlighting that most acoustic cues are derived traits. Descriptions of these sounds range from tonal calls, broadband grunts, roars, and barks to complex amplitude-modulated trills and chirps, repeated sequences, and song. Numerous species have displayed evidence of discrimination of physical traits based on acoustic characteristics, dialects, niche partitioning, vocal plasticity, anti-masking techniques, and call pattern sequencing and recognition—whether by pups, juveniles, or adults. Here, we collate data published in English to provide an overview of the pinniped families’ call characteristics, repertoires, and associated functions.
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Kaur, Rajwinder, Richa Brar, and Gagandeep Jagdev. "Comparative Analysis and Implementation of CLAHE with Proposed Technique in Retinal Images." In New Frontiers in Communication and Intelligent Systems. Soft Computing Research Society, 2021. http://dx.doi.org/10.52458/978-81-95502-00-4-9.

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The human eye is the most critical part that can be adversely affected by diabetes in the near or long run. The detection of DR (Diabetic Retinopathy) in the early stages is not that easily possible. The detection of DR primarily depends on the quality of the retinal images of the diseased person. The higher is the quality of the retinal image, the more are the chances of detection of abnormalities. The research paper elaborates on the popular CLAHE (Contrast Limited Adaptive Histogram Equalization) technique been used for enhancing the contrast of the retinal images. The research paper also anticipates a technique intended for enhancing the quality of the retinal images. The retinal images are obtained from the DRIVE (Digital Retinal Images for Vessel Extraction) dataset. The quality of enhancement achieved by using both techniques is compared and measured using three performance metrics of MSE (Mean Square Error), PSNR (Peak Signal Noise Ratio), and RMSE (Root Mean Square Error). PSNR is considered as the prominent performance metric to decide the degree of enhancement achieved. Greater is the value of the PSNR, higher is the degree of enhancement. The comparative analyses between the PSNR values obtained from both the techniques have been conducted and it has been found that the proposed technique outperforms CLAHE in enhancing the retinal images.
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Bora, Dibya Jyoti. "Enhancing HE Stain Images Through an Advanced Soft Computing-Based Adaptive Ameliorated CLAHE." In Advances in Library and Information Science. IGI Global, 2020. http://dx.doi.org/10.4018/978-1-7998-1021-6.ch014.

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HE stain images play a crucial role in the medical imaging process. Often these images are regarded as of golden standards by physicians for the quality and accuracy. These images are fuzzy by nature, and hence, traditional hard-based techniques are not able to deal with this. Thereby, a decrease in the accuracy of the analysis process may be experienced. Preprocessing of these images is utmost needed so that the fuzziness may be removed to a satisfactory level. A new approach for tackling this problem is introduced in this chapter. The proposed technique is soft computing-based advanced adaptive ameliorated CLAHE. The experimental results demonstrate the superiority of the proposed approach than the other traditional techniques.
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Sriraam, Natarajan, Leema Murali, Amoolya Girish, et al. "Classification of Breast Thermograms Using Statistical Moments and Entropy Features with Probabilistic Neural Networks." In Deep Learning and Neural Networks. IGI Global, 2020. http://dx.doi.org/10.4018/978-1-7998-0414-7.ch065.

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Breast cancer is considered as one of the life-threatening disease among woman population in developing as well as developed countries. This specific study reports on classification of breast thermograms using probabilistic neural network (PNN) with four statistical moments features mean, standard deviation, skewness and kurtosis and two entropy features, Shannon entropy and Wavelet packet entropy. The CLAHE histogram equalization algorithm with uniform and Rayleigh distributions were considered for contrast enhancement of breast thermal images. The asymmetry detection was performed by applying bilateral ratio. A total of 95 test images (normal = 53, abnormal = 42) was considered. Simulation study shows that CLAHE -RD with wavelet entropy features confirms the existence of symmetry on the right and left breast thermal images. An overall classification accuracy of 92.5% was achieved using the proposed multifeatures with PNN classifier. The proposed technique thus confirms the suitability as a screening tool for asymmetry detection as well as classification of breast thermograms.
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Sriraam, Natarajan, Leema Murali, Amoolya Girish, et al. "Classification of Breast Thermograms Using Statistical Moments and Entropy Features with Probabilistic Neural Networks." In Data Analytics in Medicine. IGI Global, 2020. http://dx.doi.org/10.4018/978-1-7998-1204-3.ch066.

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Breast cancer is considered as one of the life-threatening disease among woman population in developing as well as developed countries. This specific study reports on classification of breast thermograms using probabilistic neural network (PNN) with four statistical moments features mean, standard deviation, skewness and kurtosis and two entropy features, Shannon entropy and Wavelet packet entropy. The CLAHE histogram equalization algorithm with uniform and Rayleigh distributions were considered for contrast enhancement of breast thermal images. The asymmetry detection was performed by applying bilateral ratio. A total of 95 test images (normal = 53, abnormal = 42) was considered. Simulation study shows that CLAHE -RD with wavelet entropy features confirms the existence of symmetry on the right and left breast thermal images. An overall classification accuracy of 92.5% was achieved using the proposed multifeatures with PNN classifier. The proposed technique thus confirms the suitability as a screening tool for asymmetry detection as well as classification of breast thermograms.
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Subramani, Sangeetha, and N. Suganthi. "Kho Yolo Net." In Advances in Marketing, Customer Relationship Management, and E-Services. IGI Global, 2025. https://doi.org/10.4018/979-8-3693-6468-0.ch012.

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India's population largely depends on agriculture for their livelihood, making agricultural research vital for the nation's economy. Plant leaf disease diagnosis is essential for ensuring healthy crop production and minimizing financial losses, as plant diseases can significantly reduce crop yield and quality. Machine learning (ML), particularly image-based analysis, has revolutionized plant disease detection. To address plant leaf disease identification via image analysis, a novel KHO-YOLO Net technique has been developed. Contrast Limited Adaptive Histogram Equalization (CLAHE) is applied to plant leaf images to improve their quality. YOLO v8 is used to detect multiple diseases within a single image. YOLOv8 is optimized using the Krill Herd Optimization (KHO) technique for superior classification outcomes. The efficacy of the proposed system is compared to YOLOv3, YOLOv4, YOLOv5, and YOLOv6, with the proposed YOLOv8 demonstrating an overall accuracy improvement to 99.59%.
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Pavithra D., Vanithamani R., and Judith Justin. "Computer-Aided Diagnosis of Knee Osteoarthritis From Radiographic Images Using Random Forest Classifier." In Research Anthology on Improving Medical Imaging Techniques for Analysis and Intervention. IGI Global, 2022. http://dx.doi.org/10.4018/978-1-6684-7544-7.ch071.

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Knee osteoarthritis (OA) is a degenerative joint disease that occurs due to wear down of cartilage. Early diagnosis has a pivotal role in providing effective treatment and in attenuating further effects. This chapter aims to grade the severity of knee OA into three classes, namely absence of OA, mild OA, and severe OA, from radiographic images. Pre-processing steps include CLAHE and anisotropic diffusion for contrast enhancement and noise reduction, respectively. Niblack thresholding algorithm is used to segment the cartilage region. GLCM features like contrast, correlation, energy, homogeneity, and cartilage features such as area, medial, and lateral thickness are extracted from the segmented region. These features are fed to random forest classifier to assess the severity of OA. Performance of random forest classifier is compared with ANFIS and Naïve Bayes classifier. The classifiers are trained with 120 images and tested with 45 images. Experimental results show that random forest classifier achieves a higher accuracy of 88.8% compared to ANFIS and Naïve Bayes classifier.
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Conference papers on the topic "CLAHE technique"

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Boondach, Mintra, and Parkpoom Chaisiriprasert. "Improving Durian Leaf Disease Detection Using LAB Color Space and CLAHE Technique with YOLOv8 Integration." In 2024 8th International Conference on Information Technology (InCIT). IEEE, 2024. https://doi.org/10.1109/incit63192.2024.10810589.

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Kumari, Shweta, Ravi Kumar, Manikant Kumar, Ashish Kumar, Mithilesh Kumar Rai, and Vijay Kumar. "A Hybrid Approach for Enhancement of Underwater Images Using CLAHE and Percentile-Based Techniques." In 2024 4th International Conference on Emerging Frontiers in Electrical and Electronic Technologies (ICEFEET). IEEE, 2024. https://doi.org/10.1109/icefeet64463.2024.10867027.

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Amalia, Nurul Asmi, Aida Afira, Maria Ulfa, and Kahlil Muchtar. "Utilizing Edge Device and Streamlit for Comparative Evaluation of CLAHE-Based Underwater Image Enhancement Techniques." In 2024 IEEE 13th Global Conference on Consumer Electronics (GCCE). IEEE, 2024. https://doi.org/10.1109/gcce62371.2024.10760315.

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Intyanto, Gramandha Wega, Riski Apriyanto, Khairul Anam, Ali Rizal Chaidir, Catur Suko Sarwono, and Andrita Ceriana Eska. "UGER: Enhancing the Quality of ROUV Image Segmentation with CLAHE and Color Space-Morphology Masking Techniques." In 2024 IEEE 2nd International Conference on Electrical Engineering, Computer and Information Technology (ICEECIT). IEEE, 2024. https://doi.org/10.1109/iceecit63698.2024.10859578.

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Soni, Badal, and Prachi Mathur. "An Improved Image Dehazing Technique using CLAHE and Guided Filter." In 2020 7th International Conference on Signal Processing and Integrated Networks (SPIN). IEEE, 2020. http://dx.doi.org/10.1109/spin48934.2020.9071296.

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Nishida, Luana Amie Shimomaebara, and Pedro Moises de Sousa. "Breast Density Classification Using Convolutional Neural Networks and Analysis of the CLAHE Technique." In Workshop de Sistemas de Informação. Sociedade Brasileira de Computação, 2024. https://doi.org/10.5753/wsis.2024.33673.

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Abstract:
Breast cancer is the most common type of cancer and one of the leading causes of death worldwide. Early detection is essential to increase the chances of successful treatment, but current conventional methods still have limitations. Artificial intelligence has shown promise in aiding diagnosis. The project therefore seeks to use Convolutional Neural Networks to classify breast density, which is an important factor in the diagnosis of breast cancer. These networks learn automatically from raw data, classifying more accurately. The convolution operation and pooling layers are used to process the inputs and extract complex features. Fully connected layers classify and identify features. The dataset used was a combined dataset between INbreast and RSNA, pre-processed and using the CLAHE technique to increase the contrast of the mammograms. The end result was an accuracy of 89.29% for ResNet-50 and ShuffleNet.
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Thepade, Sudeep D., and Pravin M. Pardhi. "Mammographic Image Enhancement Using a Linear Weighted Fusion of Contrast Improvement Technique and CLAHE." In 2023 IEEE 3rd Mysore Sub Section International Conference (MysuruCon). IEEE, 2023. http://dx.doi.org/10.1109/mysurucon59703.2023.10396950.

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Rakshit, Bodhisattwa, Rounak Das, and Nilanjan Chattaraj. "Detection-Accuracy Enhancement of COVID-19 from Multi-Class Lung Diseases by Instrumenting CLAHE Integrated Deep Learning Technique." In 2022 IEEE 2nd International Symposium on Sustainable Energy, Signal Processing and Cyber Security (iSSSC). IEEE, 2022. http://dx.doi.org/10.1109/isssc56467.2022.10051405.

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Sharma, Richa, and Amit Kamra. "A Review on CLAHE Based Enhancement Techniques." In 2023 6th International Conference on Contemporary Computing and Informatics (IC3I). IEEE, 2023. http://dx.doi.org/10.1109/ic3i59117.2023.10397722.

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Sajeev, Shelda, Mariusz Bajger, and Gobert Lee. "Segmentation of Breast Masses in Local Dense Background Using Adaptive Clip Limit-CLAHE." In 2015 International Conference on Digital Image Computing: Techniques and Applications (DICTA). IEEE, 2015. http://dx.doi.org/10.1109/dicta.2015.7371305.

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