Research ArticleOpen accessEvery word in the titleFPGA IMPLEMENTATION AND ANALYSIS OF IMPULSE NOISE REDUCTION IN IMAGESP. Thirumurugan, S. Sasikumar, C. SugapriyaThe images are affected by random valued impulse noises during the image capturing and processing stages. In this study, an efficient, high performance and low hardware utilized impulse noise reduction algorithm is presented. This methodology determines the optimum direction pixels through the estimation of standard deviation. The edges in the images are preserved during the process of impulse noise detection … …American Journal of Applied Sciences, Vol. 11, Issue 7 · 19 Apr 2014 · 7,200 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleFLANN Detector Based Filtering of Images Corrupted by Impulse NoiseBanshidhar Majhi, Mowafak FathiWe present a novel non-linear scheme for image restoration based on neuro-detector using Functional Link Artificial Neural Network (FLANN) followed by an improved spatial filter. The method is applied to images corrupted by impulse noise with varying strengths and different noise probability. The neural detector is based on the concept of training or learning by examples. When trained properly, the … …Journal of Computer Science, Vol. 1, Issue 3 · 30 Sep 2005 · 7,237 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleA Novel Approach to Classify Noises in Images Using Artificial Neural NetworkT. Santhanam, S. RadhikaProblem statement: Noise identification is predominant in any digital image processing algorithms, which helps in identifying the filters to smooth the image for further processing. Approach: An Artificial Neural Network (ANN) based approach was proposed for noise identification. The suggested technique involved seclusion of the noise samples and extracts their statistical features, which was then applied to a neural network … …Journal of Computer Science, Vol. 6, Issue 5 · 31 May 2010 · 7,190 accessesView PDFCite
Research ArticleOpen accessIn the keywordsA Comprehensive Review of Medical Image Denoising: Techniques, Challenges, Applications and Future DirectionsMohit Sharma, Ayush Dogra, Anita Gupta et al.The concept of noise reduction in medical images plays a vital role in improving image quality and accuracy associated with diagnosis, and facilitating reliable automated analysis. This survey presents a structured overview of medical image denoising, beginning with foundational definitions and noise models for modalities such as MRI and CT. We critically evaluate persistent gaps, including the limited generalizability of … …Journal of Computer Science, Vol. 22, Issue 3 · 28 Mar 2026 · 1,849 accessesView PDFCite
Research ArticleOpen accessIn the keywordsNovel Fuzzy Technique for Cancer Detection in Noisy Breast Ultrasound ImagesN. Alamelumangai, J. DeviShreeProblem statement: Detecting tumor areas in breast Ultrasound (US) images is a challenging task. The occurrence of benign areas in breast may result in false identification of malignant areas which may have serious outcome. Approach: The CAD system could act as a major function in the early detection of breast cancer and could decrease the death rate among women with … …American Journal of Applied Sciences, Vol. 9, Issue 5 · 12 Mar 2012 · 6,959 accessesView PDFCite
Research ArticleOpen accessIn the keywordsWarped Optical-Flow Inter-Frame Reconstruction for Ultrasound Image EnhancementBalza Achmad, Mohd Marzuki Mustafa, Aini HussainProblem statement: Optical flow inter-frame enhancement is one of the techniques to improve the quality of ultrasound images by reducing the speckle noise. The performance depends on accuracy of the optical flow inter-frame reconstruction which is a part of the technique. The speckle noise of an ultrasound image forms certain pattern, of which size of the speckle varies depends on … …Journal of Computer Science, Vol. 7, Issue 10 · 6 Aug 2011 · 7,212 accessesView PDFCite
Research ArticleOpen accessIn the keywordsA New Discussion of Different Noises and FiltersP.N. Sundararajan, S. Sasi KumarIn digital image processing, noise acquisition and noise removal is required to enhance the quality of an image and during transmission variety of noise that affects the quality of the image. The major intension of filtering or de-noising the image is to reconstruct the detail of master image as much as possible. The metrics of the image noise removal trouble … …American Journal of Applied Sciences, Vol. 11, Issue 12 · 3 Jan 2015 · 5,973 accessesView PDFCite
Research ArticleOpen accessIn the abstractImage Pre-Processing Techniques to Improve DBT Classification Accuracy With CNN ResNet-50Qodri Aziz, Slamet Riyadi et al.Digital Breast Tomosynthesis (DBT) is a three-dimensional imaging technology that is meant to determine breast cancer more accurately than regular mammograms. But low contrast and noise can make DBT images less clear, which can make deep learning-based classification less accurate. This study seeks to assess the impact of diverse preprocessing techniques on breast cancer classification outcomes utilizing the ResNet-50 Convolutional … …Journal of Computer Science, Vol. 22, Issue 10 · 21 Oct 2026 · 349 accessesView PDFCite
Research ArticleOpen accessIn the abstractEnhancing Kidney Stone Detection Accuracy Using Image Processing and a Hybrid Convolutional Deep Belief NetworkGeetha M. N, Barkathulla A, S. Nandhini Devi et al.Automated CKD is a rapidly expanding non-communicable ailment that significantly contributes to global mortality and morbidity. CKD impacts more than 10% of the worldwide population, leading to millions of deaths annually. This paper proposes an enhanced deep learning model for renal disease detection that integrates convolutional and involution layers to enhance classification accuracy. CKD is a worldwide health issue characterised … …Journal of Computer Science, Vol. 22, Issue 10 · 9 Oct 2026 · 749 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Adaptive Detail Preserving Modified Progressive Pca Thresholding Based Image DenoisingN. Anilkumar, S. Radhakrishnan, Shaik Syed Basha et al.Radiologists use medical imaging tools to assess the anatomy and function of interior organs. However, medical images are frequently distorted by various types of noise generated during the capture, transmission, and reconstruction operations, which can dramatically reduce image quality and hide critical diagnostic features. As a result, developing effective denoising algorithms that suppress noise while maintaining structural information remains a … …Journal of Computer Science, Vol. 22, Issue 8 · 8 Sep 2026 · 529 accessesView PDFCite