Contrast in image processing is usually defined as a ratio between the darkest and the brightest spots of an image. In this paper we introduce a different contrast definition. The newly introduced Global Contrast Factor (GCF) corresponds closer to the human perception of contrast. GCF uses contrasts at various resolution levels in order to compute overall contrast. Experiments were conducted in...

In recent years, brain tumors become the leading cause of death in the world. Detection and rapid classification of this tumor are very important and may indicate the likely diagnosis and treatment strategy. In this paper, we propose deep learning techniques based on the combinations of pre-trained VGG-16 CNNs to classify three types of brain tumors (i.e., meningioma, glioma, and pituitary tumo...

We study the focusing properties of a two dimensional complex square-lattice photonic crystal (PC) comprising air holes immersed in Ge medium. The finite difference time domain (FDTD) method is utilized to calculate the dispersion band diagram and to simulate the image formation incorporating the perfectly matched layer (PML) boundary condition. In contrast to the common square PCs with the sam...

Infrared (IR) and visible image fusion is an important data processing technique that can accurately comprehensively integrate the thermal radiation texture details of source images. However, existing methods neglect high-contrast problem, leading to suboptimal performance when target information in IR images replaced by To address this limitation, we propose a contrast-balanced framework for f...

Introduction: Using contrast medium in diagnosis and identifying of an organ from its surrounding tissue is very useful. These contrast mediums alter radiation absorption of studied organs. The aim of this study is to identify the influences of contrast media in treatment planning system of the pelvis.   Materials and Methods: Seven patients with pelvis area ...

Introduction: All of the Imaging modalities have advantages and disadvantages alone. So if we want to have the best and perfect image, combining these modalities produces something we desired. PET-MR images consist of morphologic and metabolic data. MRI and PET provide high spatial and contrast resolution and high sensitivity and molecular information respectively. Hybrid PET-...