Digital images are corrupted with noise, and image denoising is an important step in image processing modules. In this review, the latest developments in filtering methods for color image restoration are analyzed. These algorithms are compared in ...

Biometric recognition based on the full face is an extensive research area. However, using only partially visible faces, such as in the case of veiled-persons, is a challenging task. Deep convolutional neural network (CNN) is used in this work to extract ...

In this paper, we present an efficient dermoscopic image segmentation method based on the linearisation of gamma-correction, and convolutional neural networks. Linearisation of gamma-correction is helpful to enhance low-intensity regions of skin lesion ...

Visualization of inner gastrointestinal (GI) tract is an important aspect in diagnosis of diseases such as the bleeding and colon cancer. Wireless capsule endoscopy (WCE) provides painless imaging of the GI tract without much discomfort to ...

Segmenting microvascular structures is an important requirement in understanding angioadaptation by which vascular networks remodel their morphological structures. Accurate segmentation for separating microvasculature structures is important in ...

Medical X-ray images are prevalent and are the least expensive diagnostic imaging method available widely. The handling of film processing and digitization introduces noise in X-ray images and suppressing such noise is an important step in medical image ...

Computer aided diagnosis (CAD) systems are important in obtaining precision medicine and patient driven solutions for various diseases. One of the main brain tumor is the Glioblastoma multiforme (GBM) and histopathological tissue images can provide ...

Automatic segmentation of cerebral hemispheres in magnetic resonance MR brain images help to quantify the brain asymmetry and correct several MR brain deformities. The detection of mid-sagittal plane MSP in human brain image is necessary to segment the ...

This work discusses the performance of a color decomposition based active contours for segmenting cell nuclei from glioma histopathology. By combining a nuclear staining information obtained from color decomposition with fast variational active contours ...

Restoring damaged images is an important problem in image processing and has been studied for applications such as inpainting missing regions, art restoration. In this work, we consider a modified (fuzzy transform) F-transform for restoration of ...

Nonlinear anisotropic diffusion is widely used in image processing and computer vision for various problems. One of the basic and important problem is that of restoring noisy images and diffusion filters are an important class of denoising ...

We study an efficient texture image segmentation model for multichannel images using a local feature fitting based active contours scheme. Using a chromaticity-brightness decomposition, we propose a flexible segmentation approach using multi-channel ...

We propose a segmentation scheme for digital color images using vectorial multiscale anisotropic diffusion. By integrating the edge information, diffusion based schemes can remove noise effectively and create fine to coarse set of images known as scale-...