Le Thi Thanh

TL;DR: 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 and results indicate the authors obtain artifact free edge preserving restorations.

TL;DR: By combining the proposed initial boundary generation method based on the Canny edge detector, the Chan-Vese model to segment biomedical images is implemented and results indicate improved segmentation results and compare different edge detectors in terms of performance.

TL;DR: A single image dehazing method based on combination of adaptive histogram equalization, HSV color model and linearization of Gamma correction that dehazes effectively and can compete with other state-of-the-art dehazed methods.

TL;DR: This paper proposes a parameter estimation method based on characteristics of the salt-and-pepper noise that is especially effective for the images without very high contrast and with high noise level.

TL;DR: A chest X-Ray image denoising method based on Total variation regularization with implementation on the Nesterov optimization method and based on the image quality assessment metrics confirmed that the proposed method outperforms other compared Denoising methods.