In this paper, we present an extensive review on deep learning methods for image
restoration tasks. Deep learning techniques, led by convolutional neural networks, have …

The current literature documents a plethora of image denoising techniques in the fields of
medical imaging, remote sensing, biometrics, surveillance and vegetation mapping …

Deep learning has achieved notable performance in the denoising task of low-quality
medical images and the detection task of lesions, respectively. However, existing low-quality …

In this article, a focus is laid on the hybridization of various noise removal kernels that are
used in the normalization of the noise in the medical MR images which is acquainted into …

Digital images are impression of a particular scenario composed of picture elements in form
of pixels. Image restoration is a technique that is used to reinstitute the source or original …

Video/image compression codecs utilize the characteristics of the human visual system and
its varying sensitivity to certain frequencies, brightness, contrast, and colors to achieve high …

Background and Objective: Segmentation of the femur in Dual-Energy X-ray (DXA) images
poses challenges due to reduced contrast, noise, bone shape variations, and inconsistent X …

This paper proposes an image filtering method to remove the noises in medical images in a
controlled manner. To achieve this goal, the optimal parameters of the conventional filters …

Medical image processing generally contains high components of noise produced by
interference, compression and use of imperfect instrument during acquisition or …

Purpose In medical imaging acquisitions, the image degradation process is composed of the
blur and noise resulting in the imaging framework. Regularization methods are essential to …