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  • Open Access

    ARTICLE

    Balanced GHM Mutiwavelet Transform Based Contrast Enhancement Technique for Dark Images Using Dynamic Stochastic Resonance

    S. Deivalakshmi*, P. Palanisamy1, X. Z. Gao2

    Intelligent Automation & Soft Computing, Vol.25, No.3, pp. 459-471, 2019, DOI:10.31209/2018.100000001

    Abstract The main aim of this paper is to propose a new technique for enhancing the contrast of dark images using Dynamic Stochastic Resonance (DSR) and Multi Wavelet Transform (MWT), which is computationally more efficient than the conventional methods. In the work, for enhancing the contrast of dark images, the intrinsic noise (darkness) of dark images has been used. The proposed MWT-based DSR scheme (MWT-DSR) can yield better performances in terms of visual information and color preservation than already reported techniques. The desired output response is validated by the Relative Contrast Enhancement Factor (F), Perceptual Quality Measures (PQM) and Color Enhancement… More >

  • Open Access

    ARTICLE

    A General Framework of Reversible Data Hiding with Controlled Contrast Enhancement

    Shaowei Weng1, 2, *, Yiyun Liu1, Yunqing Shi3, Bo Ou4, Chunyu Zhang5, Cuiping Wang6

    CMC-Computers, Materials & Continua, Vol.62, No.1, pp. 157-177, 2020, DOI:10.32604/cmc.2020.05681

    Abstract This paper proposes a two-step general framework for reversible data hiding (RDH) schemes with controllable contrast enhancement. The first step aims at preserving visual perception as much as possible on the basis of achieving high embedding capacity (EC), while the second step is used for increasing image contrast. In the second step, some peak-pairs are utilized so that the histogram of pixel values is modified to perform histogram equalization (HE), which would lead to the image contrast enhancement. However, for HE, the utilization of some peak-pairs easily leads to over-enhanced image contrast when a large number of bits are embedded.… More >

  • Open Access

    ARTICLE

    A Novel Reversible Data Hiding Scheme Based on Lesion Extraction and with Contrast Enhancement for Medical Images

    Xingxing Xiao1, Yang1,*, Rui Li2, Weiming Zhang3

    CMC-Computers, Materials & Continua, Vol.60, No.1, pp. 101-115, 2019, DOI:10.32604/cmc.2019.05293

    Abstract The medical industry develops rapidly as science and technology advance. People benefit from medical resource sharing, but suffer from privacy leaks at the same time. In order to protect patients’ privacy and improve quality of medical images, a novel reversible data hiding (RDH) scheme based on lesion extraction and with contrast enhancement is proposed. Furthermore, the proposed scheme can enhance the contrast of medial image's lesion area directly and embed high-capacity privacy data reversibly. Different from previous segmentation methods, this scheme first adopts distance regularized level set evolution (DRLSE) to extract lesion and targets at the lesion area accurately for… More >

  • Open Access

    ARTICLE

    Retinal Vessel Extraction Framework Using Modified Adaboost Extreme Learning Machine

    B. V. Santhosh Krishna1, *, T. Gnanasekaran2

    CMC-Computers, Materials & Continua, Vol.60, No.3, pp. 855-869, 2019, DOI:10.32604/cmc.2019.07585

    Abstract An explicit extraction of the retinal vessel is a standout amongst the most significant errands in the field of medical imaging to analyze both the ophthalmological infections, for example, Glaucoma, Diabetic Retinopathy (DR), Retinopathy of Prematurity (ROP), Age-Related Macular Degeneration (AMD) as well as non retinal sickness such as stroke, hypertension and cardiovascular diseases. The state of the retinal vasculature is a significant indicative element in the field of ophthalmology. Retinal vessel extraction in fundus imaging is a difficult task because of varying size vessels, moderately low distinction, and presence of pathologies such as hemorrhages, microaneurysms etc. Manual vessel extraction… More >

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