Bhawna Goyal^1,*, Ayush Dogra², Rahul Khoond¹, Dawa Chyophel Lepcha¹, Vishal Goyal³, Steven L. Fernandes⁴

CMC-Computers, Materials & Continua, Vol.76, No.1, pp. 311-327, 2023, DOI:10.32604/cmc.2023.038398 - 08 June 2023

Abstract The synthesis of visual information from multiple medical imaging inputs to a single fused image without any loss of detail and distortion is known as multimodal medical image fusion. It improves the quality of biomedical images by preserving detailed features to advance the clinical utility of medical imaging meant for the analysis and treatment of medical disorders. This study develops a novel approach to fuse multimodal medical images utilizing anisotropic diffusion (AD) and non-subsampled contourlet transform (NSCT). First, the method employs anisotropic diffusion for decomposing input images to their base and detail layers to coarsely… More >

N. A. Lawrance^*, T. S. Shiny Angel

Computer Systems Science and Engineering, Vol.46, No.3, pp. 3439-3455, 2023, DOI:10.32604/csse.2023.030311 - 03 April 2023

Abstract The practice of integrating images from two or more sensors collected from the same area or object is known as image fusion. The goal is to extract more spatial and spectral information from the resulting fused image than from the component images. The images must be fused to improve the spatial and spectral quality of both panchromatic and multispectral images. This study provides a novel picture fusion technique that employs L0 smoothening Filter, Non-subsampled Contour let Transform (NSCT) and Sparse Representation (SR) followed by the Max absolute rule (MAR). The fusion approach is as follows: More >

T. Manikandan¹, S. Karthikeyan^2,*, J. Jai Jaganath Babu³, G. Babu⁴

Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 2755-2771, 2023, DOI:10.32604/iasc.2023.030497 - 17 August 2022

Abstract Signal to noise ratio in ultrasound medical images captured through the digital camera is poorer, resulting in an inaccurate diagnosis. As a result, it needs an efficient despeckling method for ultrasound images in clinical practice and telemedicine. This article proposes a novel adaptive fuzzy filter based on the directionality and translation invariant property of the Non-Sub sampled Contour-let Transform (NSCT). Since speckle-noise causes fuzziness in ultrasound images, fuzzy logic may be a straightforward technique to derive the output from the noisy images. This filtering method comprises detection and filtering stages. First, image regions classify at… More >

Kandasamy Kittusamy^*, Latha Shanmuga Vadivu Sampath Kumar

Computer Systems Science and Engineering, Vol.44, No.3, pp. 1989-2005, 2023, DOI:10.32604/csse.2023.026501 - 01 August 2022

Abstract Medical Image Fusion is the synthesizing technology for fusing multimodal medical information using mathematical procedures to generate better visual on the image content and high-quality image output. Medical image fusion represents an indispensible role in fixing major solutions for the complicated medical predicaments, while the recent research results have an enhanced affinity towards the preservation of medical image details, leaving color distortion and halo artifacts to remain unaddressed. This paper proposes a novel method of fusing Computer Tomography (CT) and Magnetic Resonance Imaging (MRI) using a hybrid model of Non Sub-sampled Contourlet Transform (NSCT) and… More >

Reena Thomas^1,*, M. Sucharitha²

Intelligent Automation & Soft Computing, Vol.33, No.2, pp. 879-889, 2022, DOI:10.32604/iasc.2022.024070 - 08 February 2022

Abstract The major intention of this work is to introduce a novel hybrid image watermarking technique for RGB color images. This hybrid watermarking algorithm uses two transforms such as Contourlet and Gould transform. The Contourlet transform is used as first stage while the Gould transform is used as second stage. In the watermark embedding phase, the R, G and B channels are transformed using Contourlet transform. The bandpass directional sub band coefficients of Contourlet transformed image are then divided into sub-blocks. The sub-blocks are then transformed using Gould transform and the watermark information is embedded on More >

K. Lakshminarayanan¹, N. Muthukumaran¹, Y. Harold Robinson², Vimal Shanmuganathan³, Seifedine Kadry⁴, Yunyoung Nam^5,*

CMC-Computers, Materials & Continua, Vol.67, No.3, pp. 3045-3055, 2021, DOI:10.32604/cmc.2021.014370 - 01 March 2021

Abstract Hookworm is an illness caused by an internal sponger called a roundworm. Inferable from deprived cleanliness in the developing nations, hookworm infection is a primary source of concern for both motherly and baby grimness. The current framework for hookworm detection is composed of hybrid convolutional neural networks; explicitly an edge extraction framework alongside a hookworm classification framework is developed. To consolidate the cylindrical zones obtained from the edge extraction framework and the trait map acquired into the hookworm scientific categorization framework, pooling layers are proposed. The hookworms display different profiles, widths, and bend directions. These More >

V. Vidya Lakshmi^1,*, J. S. Leena Jasmine²

Computer Systems Science and Engineering, Vol.37, No.2, pp. 233-245, 2021, DOI:10.32604/csse.2021.015700 - 01 March 2021

Abstract Melanoma or skin cancer is the most dangerous and deadliest disease. As the incidence and mortality rate of skin cancer increases worldwide, an automated skin cancer detection/classification system is required for early detection and prevention of skin cancer. In this study, a Hybrid Artificial Intelligence Model (HAIM) is designed for skin cancer classification. It uses diverse multi-directional representation systems for feature extraction and an efficient Exponentially Weighted and Heaped Multi-Layer Perceptron (EWHMLP) for the classification. Though the wavelet transform is a powerful tool for signal and image processing, it is unable to detect the intermediate More >

Xiaoying Chen^{1, 2, *}, Shijun Zhao², Xiaolei Wang², Xuejin Sun², Jing Feng², Nan Ye³

CMC-Computers, Materials & Continua, Vol.61, No.2, pp. 861-875, 2019, DOI:10.32604/cmc.2019.06230

Abstract It is important to extract texture feature from the ground-base cloud image for cloud type automatic detection. In this paper, a new method is presented to capture the contour edge, texture and geometric structure of cloud images by using Contourlet and the power spectrum analysis algorithm. More abundant texture information is extracted. Cloud images can be obtained a multiscale and multidirection decomposition. The coefficient matrix from Contourlet transform of ground nephogram is calculated. The energy, mean and variance characteristics calculated from coefficient matrix are composed of the feature information. The frequency information of the data More >