Meng Yang¹, Jingbing Li^1,2,*, Uzair Aslam Bhatti^1,2, Chunyan Shao¹, Yen-Wei Chen³

CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 5539-5554, 2023, DOI:10.32604/cmc.2023.036904 - 29 April 2023

Abstract With the development of digitalization in healthcare, more and more information is delivered and stored in digital form, facilitating people’s lives significantly. In the meanwhile, privacy leakage and security issues come along with it. Zero watermarking can solve this problem well. To protect the security of medical information and improve the algorithm’s robustness, this paper proposes a robust watermarking algorithm for medical images based on Non-Subsampled Shearlet Transform (NSST) and Schur decomposition. Firstly, the low-frequency subband image of the original medical image is obtained by NSST and chunked. Secondly, the Schur decomposition of low-frequency blocks… More >

S. Mohan Kumar^*, T. Kumanan

Computer Systems Science and Engineering, Vol.44, No.1, pp. 833-844, 2023, DOI:10.32604/csse.2023.022385 - 01 June 2022

Abstract The main cause of skin cancer is the ultraviolet radiation of the sun. It spreads quickly to other body parts. Thus, early diagnosis is required to decrease the mortality rate due to skin cancer. In this study, an automatic system for Skin Lesion Classification (SLC) using Non-Subsampled Shearlet Transform (NSST) based energy features and Support Vector Machine (SVM) classifier is proposed. At first, the NSST is used for the decomposition of input skin lesion images with different directions like 2, 4, 8 and 16. From the NSST’s sub-bands, energy features are extracted and stored in More >

Hilly Gohain Baruah^*, Vijay Kumar Nath, Deepika Hazarika

CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.1, pp. 137-164, 2022, DOI:10.32604/cmes.2022.018339 - 24 January 2022

Abstract With the increasing popularity of high-resolution remote sensing images, the remote sensing image retrieval (RSIR) has always been a topic of major issue. A combined, global non-subsampled shearlet transform (NSST)-domain statistical features (NSSTds) and local three dimensional local ternary pattern (3D-LTP) features, is proposed for high-resolution remote sensing images. We model the NSST image coefficients of detail subbands using 2-state laplacian mixture (LM) distribution and its three parameters are estimated using Expectation-Maximization (EM) algorithm. We also calculate the statistical parameters such as subband kurtosis and skewness from detail subbands along with mean and standard deviation… More >

Peizhou Yan¹, Jiancheng Zou^2,*, Zhengzheng Li¹, Xin Yang³

Intelligent Automation & Soft Computing, Vol.28, No.1, pp. 213-225, 2021, DOI:10.32604/iasc.2021.016201 - 17 March 2021

Abstract Within the application of driving assistance systems, the detection of driver’s facial features in the cab for a spectrum of luminosities is mission critical. One method that addresses this concern is infrared and visible image fusion. Its purpose is to generate an aggregate image which can granularly and systematically illustrate scene details in a range of lighting conditions. Our study introduces a novel approach to this method with marked improvements. We utilize non-subsampled shearlet transform (NSST) to obtain the low and high frequency sub-bands of infrared and visible imagery. For the low frequency sub-band fusion,… More >