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  • Open Access

    ARTICLE

    Super-Resolution Based on Curvelet Transform and Sparse Representation

    Israa Ismail1,*, Mohamed Meselhy Eltoukhy1,2, Ghada Eltaweel1

    Computer Systems Science and Engineering, Vol.45, No.1, pp. 167-181, 2023, DOI:10.32604/csse.2023.028906 - 16 August 2022

    Abstract Super-resolution techniques are used to reconstruct an image with a high resolution from one or more low-resolution image(s). In this paper, we proposed a single image super-resolution algorithm. It uses the nonlocal mean filter as a prior step to produce a denoised image. The proposed algorithm is based on curvelet transform. It converts the denoised image into low and high frequencies (sub-bands). Then we applied a multi-dimensional interpolation called Lancozos interpolation over both sub-bands. In parallel, we applied sparse representation with over complete dictionary for the denoised image. The proposed algorithm then combines the dictionary More >

  • Open Access

    ARTICLE

    An Optimised Defensive Technique to Recognize Adversarial Iris Images Using Curvelet Transform

    K. Meenakshi1,*, G. Maragatham2

    Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 627-643, 2023, DOI:10.32604/iasc.2023.026961 - 06 June 2022

    Abstract Deep Learning is one of the most popular computer science techniques, with applications in natural language processing, image processing, pattern identification, and various other fields. Despite the success of these deep learning algorithms in multiple scenarios, such as spam detection, malware detection, object detection and tracking, face recognition, and automatic driving, these algorithms and their associated training data are rather vulnerable to numerous security threats. These threats ultimately result in significant performance degradation. Moreover, the supervised based learning models are affected by manipulated data known as adversarial examples, which are images with a particular level… More >

  • Open Access

    ARTICLE

    Unconstrained Hand Dorsal Veins Image Database and Recognition System

    Mustafa M. Al Rifaee1,*, Mohammad M. Abdallah1, Mosa I. Salah2, Ayman M. Abdalla1

    CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 5063-5073, 2022, DOI:10.32604/cmc.2022.030033 - 28 July 2022

    Abstract Hand veins can be used effectively in biometric recognition since they are internal organs that, in contrast to fingerprints, are robust under external environment effects such as dirt and paper cuts. Moreover, they form a complex rich shape that is unique, even in identical twins, and allows a high degree of freedom. However, most currently employed hand-based biometric systems rely on hand-touch devices to capture images with the desired quality. Since the start of the COVID-19 pandemic, most hand-based biometric systems have become undesirable due to their possible impact on the spread of the pandemic.… More >

  • Open Access

    ARTICLE

    Convolutional Neural Networks Based Video Reconstruction and Computation in Digital Twins

    M. Kavitha1, B. Sankara Babu2, B. Sumathy3, T. Jackulin4, N. Ramkumar5, A. Manimaran6, Ranjan Walia7, S. Neelakandan8,*

    Intelligent Automation & Soft Computing, Vol.34, No.3, pp. 1571-1586, 2022, DOI:10.32604/iasc.2022.026385 - 25 May 2022

    Abstract With the advancement of communication and computing technologies, multimedia technologies involving video and image applications have become an important part of the information society and have become inextricably linked to people's daily productivity and lives. Simultaneously, there is a growing interest in super-resolution (SR) video reconstruction techniques. At the moment, the design of digital twins in video computing and video reconstruction is based on a number of difficult issues. Although there are several SR reconstruction techniques available in the literature, most of the works have not considered the spatio-temporal relationship between the video frames. With… More >

  • Open Access

    ARTICLE

    Fast and Accurate Thoracic SPECT Image Reconstruction

    Afef Houimli1,*, IssamBen Mhamed2, Bechir Letaief1,3,4, Dorra Ben-Sellem1,3,4

    CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.2, pp. 881-904, 2022, DOI:10.32604/cmes.2022.016705 - 14 March 2022

    Abstract In Single-Photon Emission Computed Tomography (SPECT), the reconstructed image has insufficient contrast, poor resolution and inaccurate volume of the tumor size due to physical degradation factors. Generally, nonstationary filtering of the projection or the slice is one of the strategies for correcting the resolution and therefore improving the quality of the reconstructed SPECT images. This paper presents a new 3D algorithm that enhances the quality of reconstructed thoracic SPECT images and reduces the noise level with the best degree of accuracy. The suggested algorithm is composed of three steps. The first one consists of denoising… More >

  • Open Access

    ARTICLE

    Curvelet Transform Based on Edge Preserving Filter for Retinal Blood Vessel Segmentation

    Sonali Dash1, Sahil Verma2,*, Kavita2, N. Z. Jhanjhi3, Mehedi Masud4, Mohammed Baz5

    CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2459-2476, 2022, DOI:10.32604/cmc.2022.020904 - 07 December 2021

    Abstract Segmentation of vessel in retinal fundus images is a primary step for the clinical identification for specific eye diseases. Effective diagnosis of vascular pathologies from angiographic images is thus a vital aspect and generally depends on segmentation of vascular structure. Although various approaches for retinal vessel segmentation are extensively utilized, however, the responses are lower at vessel's edges. The curvelet transform signifies edges better than wavelets, and hence convenient for multiscale edge enhancement. The bilateral filter is a nonlinear filter that is capable of providing effective smoothing while preserving strong edges. Fast bilateral filter is… More >

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