Images captured from a single or multiple imaging sensors with considerable focus or
numerous exposures of the same or different modalities do not provide all relevant …

Image fusion is a long-established and well-known study area of digital image processing.
The reason is its substantial approach in several practical applications in which multi-focus …

Nowadays image processing and machine vision fields have become important research
topics due to numerous applications in almost every field of science. Performance in these …

Multi-focus image fusion is a technique of combining two images of the same scene with
diverse focuses into a single image. The single fused image has greater depth of field than …

Abstract Machine learning and deep learning are finding applications in various computer
vision problems such as object recognition, detection, and visual tracking. In addition, in …

Image fusion combines images with complementary information to generate an informative
image. In this study, we have developed Ensemble-Individual-Features (Ens-IF) for multi …

Maximum likelihood classifier (MLC) and support vector machines (SVMs) are commonly
used supervised classification methods in remote sensing applications. MLC is a parametric …

Image fusion combines complementary information for several input images. To obtain
useful information from two misaligned images, registration is required. A hybrid textural …

This paper presents a novel methodology for enhancement of macular region using sparse
representation of segmented macular region and super resolution of Fundus Fluorescein …

In the fields of bioinformatics and drug discovery, prediction of bacterial proteins is an
important research. We proposed a novel classifier ensemble scheme for the prediction of …