Nguyen Ngoc Hien - Academia.edu (original) (raw)

Papers by Nguyen Ngoc Hien

The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences

Image restoration with regularization models is very popular in the image processing literature. ... more Image restoration with regularization models is very popular in the image processing literature. Total variation (TV) is one of the important edge preserving regularization models used, however, to obtain optimal restoration results the regularization parameter needs to be set appropriately. We propose here a new parameter estimation approach for total variation based image restoration. By utilizing known noise levels we compute the regularization parameter by reducing the similarity between residual and noise variances. We use the split Bregman algorithm for the total variation along with this automatic parameter estimation step to obtain a very fast restoration scheme. Experimental results indicate the proposed parameter estimation obtained better denoised images and videos in terms of PSNR and SSIM measures and the computational overload is less compared with other approaches.

2020 IEEE Eighth International Conference on Communications and Electronics (ICCE), 2021

Image dehazing is an important problem and it is useful as a preprocessing step in various automa... more Image dehazing is an important problem and it is useful as a preprocessing step in various automatic image analysis systems. The goal of image dehazing is the quality improvement of digital images by removing haze across the scene. In the present work, we consider an automatic image dehazing approach that is based on optimal color channels and nonlinear transformations. The proposed dehazing approach can remove haze fast and effectively with features preservation. In our experiments, we compare the image dehazing results with related image dehazing methods from the literature. Visual assessments, as well as quantitative assessments, are also done to show the improvements obtained by the dehazing model across different natural images. Obtained experimental results indicate that the dehazing approach proposed here performs better than other dehazing models in terms of overall better visual quality and higher blind image quality metric values.

2019 6th NAFOSTED Conference on Information and Computer Science (NICS), 2019

We propose an image denoising method by combining overlapping group sparsity and second-order tot... more We propose an image denoising method by combining overlapping group sparsity and second-order total variation regularization. The method is named OGS-SOTV (image denoising method based on Overlapping Group Sparsity and Second-Order Total Variation regularization). The method utilizes performance of noise removal of overlapping group sparsity and performance of artifacts elimination of second-order total variation. A regularization parameter estimation is also proposed to implement the method automatically. In experiments, we compare denoising results of OGS-SOTV with ones of other similar methods. Results confirmed that OGS-SOTV works effectively and outperforms other similar denoising methods.

2019 11th International Conference on Knowledge and Systems Engineering (KSE), 2019

We propose a fast denoising algorithm for X-Ray images with variance stabilizing transformations.... more We propose a fast denoising algorithm for X-Ray images with variance stabilizing transformations. The variance stabilizing transformations are used to transform Poisson noisy images to Gaussian noisy images. Therefore, we can utilize advantages of the fast denoising algorithm based on the alternative direction method of multipliers. In experiments, we evaluate denoising quality by the Peak signal-to-noise ratio and the Structure Similarity metrics. Comparing results show that our method outperforms other similar denoising methods.

2019 6th International Conference on Electrical and Electronics Engineering (ICEEE), 2019

In medical image processing, the skin lesion segmentation problem plays a vital role, because it ... more In medical image processing, the skin lesion segmentation problem plays a vital role, because it is necessary to improve quality of extracting skin lesion features to classify the skin lesion. Hence, imaging diagnosis systems can detect skin cancer early. It is necessary to treat the skin cancer, especially, melanoma – one of the most dangerous form of skin cancer. In this paper, we proposed two adaptive methods to estimate the global threshold used for skin lesion segmentation based on normalization of the color models: RGB and XYZ. The skin lesion segmentation based on our proposed methods gives better result than the Otsu segmentation method regarding the grayscale model. This comparison is assessed on popular metrics for image segmentation, such as Dice and Jaccard scores. Experiments are tested on the famous ISIC dataset.

Frontiers in Intelligent Computing: Theory and Applications, 2019

Image segmentation is an important problem in image processing that has a wide range of applicati... more Image segmentation is an important problem in image processing that has a wide range of applications in medicine, biomedicine and other fields of science and engineering. During the non-learning-based approaches, the techniques based on the partial differential equations and calculus of variation have attracted a lot of attention and acquired many achievements. Among the variational models, the Chan-Vese variational segmentation is a well-known model to solve the image segmentation problem. The level set methods are highly accurate methods to solve this model, and they do not depend on the edges. However, the performance of these methods depends on the level set function and its initial boundary too much. In this paper, we propose automatic initial boundary generation methods based on the edge detectors: Sobel, Prewitt, Roberts and Canny. In the experiments, we prove that among the four proposed initial boundary generation methods, the method based on the Canny edge detector brings the highest performance for the segmentation method. By combining the proposed initial boundary generation method based on the Canny edge detector, we implement the Chan-Vese model to segment biomedical images. Experimental results indicate we obtain improved segmentation results and compare different edge detectors in terms of performance.

Intelligent Computing in Engineering, 2020

In this article, we study and propose an adaptive thresholding segmentation method for dermoscopi... more In this article, we study and propose an adaptive thresholding segmentation method for dermoscopic images with Gabor filters and Principal Component Analysis. The Gabor filters is used for extracting statistical features of image and the Principal Component Analysis is applied for transforming features to various bases. In experiments, we implement tests with the ISIC dataset. Segmentation results are assessed by the Dice and the Jaccard similarities. We also compare the proposed method to other similar methods to prove its own effectiveness.

Optik, 2020

Abstract In this article, we propose an adaptive total variation (TV) regularization model for sa... more Abstract In this article, we propose an adaptive total variation (TV) regularization model for salt and pepper denoising in digital images. The adaptive TV denoising method is developed based on the general regularized image restoration model with L1 fidelity for handling salt and pepper noise model. An estimation for regularization parameter is also proposed based on the characteristics of the salt and pepper noise. We implement the proposed adaptive TV-L1 regularization model efficiently for image denoising using the primal dual gradient method. In the experiments, the full-reference image quality assessment metrics are used for evaluating denoising quality across various noise levels in different synthetic and real images. The denoising results are compared to other similar salt and pepper image denoising methods and our results indicate we obtain artifact free edge preserving restorations.

Journal of Digital Imaging, 2019

According to statistics of the American Cancer Society, in 2015, there are about 91,270 American ... more According to statistics of the American Cancer Society, in 2015, there are about 91,270 American adults diagnosed with melanoma of the skin. For the European Union, there are over 90,000 new cases of melanoma annually. Although melanoma only accounts for about 1% of all skin cancers, it causes most of the skin cancer deaths. Melanoma is considered one of the fastest-growing forms of skin cancer, and hence the early detection is crucial, as early detection is helpful and can provide strong recommendations for specific and suitable treatment regimens. In this work, we propose a method to detect melanoma skin cancer with automatic image processing techniques. Our method includes three stages: pre-process images of skin lesions by adaptive principal curvature, segment skin lesions by the colour normalisation and extract features by the ABCD rule. We provide experimental results of the proposed method on the publicly available International Skin Imaging Collaboration (ISIC) skin lesions dataset. The acquired results on melanoma skin cancer detection indicates that the proposed method has high accuracy, and overall, a good performance: for the segmentation stage, the accuracy, Dice, Jaccard scores are 96.6%, 93.9% and 88.7%, respectively; and for the melanoma detection stage, the accuracy is up to 100% for a selected subset of the ISIC dataset.

Journal of Clinical Oncology, 2002

PURPOSE: In 1992, the Early Breast Cancer Trialists’ Collaborative Group reported that a meta-ana... more PURPOSE: In 1992, the Early Breast Cancer Trialists’ Collaborative Group reported that a meta-analysis of six randomized trials in European and North American women begun from 1948 to 1972 demonstrated disease-free and overall survival benefit from adjuvant ovarian ablation. Approximately 350,000 new cases of breast cancer are diagnosed annually in premenopausal Asian women who have lower levels of estrogen than western women. PATIENTS AND METHODS: From 1993 to 1999, we recruited 709 premenopausal women with operable breast cancer (652 from Vietnam, 47 from China) to a randomized clinical trial of adjuvant oophorectomy and tamoxifen (20 mg orally every day) for 5 years or observation and this combined hormonal treatment on recurrence. At later dates estrogen- and progesterone-receptor protein assays by immunohistochemistry were performed for 470 of the cases (66%). RESULTS: Treatment arms were well balanced. With a median follow-up of 3.6 years, there have been 84 events and 69 deat...

Chemosphere, 2009

The aim of this study was to assess the adverse effects of enrofloxacin (EF) on Tra catfish, Pang... more The aim of this study was to assess the adverse effects of enrofloxacin (EF) on Tra catfish, Pangasianodon hypophthalmus, in relation with density stress. Fish were held at 40, 80 or 120 fish m(-3) and fed with pellets containing either 1 g kg(-1) EF or no EF. Antibiotic exposure lasted 7d and all fish were fed without EF for another 7-d recovery period. Fish were sampled at 3, 7, 8, 10 and 14 d after the beginning of EF exposure. Lipid peroxidation (LPO) and total glutathione (GSH) levels, catalase (CAT), glutathione-s-transferase (GST) and acetylcholine-esterase (AChE) activities were assessed in gill, brain, liver and muscle. At day 7, LPO levels in gills of EF-fish reared at low or high density were significantly more than 5-fold higher than their respective control. On the contrary, LPO in gills of EF-fish reared at medium density was significantly 3-fold lower than the control fish. Similarly, CAT activities in gills of EF-fish reared under low or high density were higher than in their control groups, while this activity was lower in EF-fish of the medium density group. AChE activities in muscles of EF-fish reared at low or high density were lower than controls at days 3 and 7, respectively. These results suggest that EF exposure may lead to disorders like lipid peroxidation and neural dysfunction in fish. However, when reared under lower stress condition (medium density), they may cope better with EF-induced stress than chronically stressed fish (low or high density).