Image segmentation is one of the most important tasks in medical image analysis and is
often the first and the most critical step in many clinical applications. In brain MRI analysis …

We summarize the various strands of research on peripheral vision and relate them to
theories of form perception. After a historical overview, we describe quantifications of the …

Traditional feature matching methods, such as scale-invariant feature transform (SIFT),
usually use image intensity or gradient information to detect and describe feature points; …

Co-registration of multimodal remote sensing (RS) images (eg, optical, infrared, LiDAR, and
SAR) is still an ongoing challenge because of nonlinear radiometric differences (NRD) and …

Automatic registration of multimodal remote sensing data [eg, optical, light detection and
ranging (LiDAR), and synthetic aperture radar (SAR)] is a challenging task due to the …

This paper investigates two fundamental problems in computer vision: contour detection and
image segmentation. We present state-of-the-art algorithms for both of these tasks. Our …

Image quality assessment (IQA) aims to use computational models to measure the image
quality consistently with subjective evaluations. The well-known structural similarity index …

Oriented filters are useful in many early vision and image processing tasks. One often needs
to apply the same filter, rotated to different angles under adaptive control, or wishes to …

We propose a two-class classification model for grou**. Human segmented natural
images are used as positive examples. Negative examples of grou** are constructed by …

Image features such as step edges, lines and Mach bands all give rise to points where the
Fourier components of the image are maximally in phase. The use of phase congruency for …