introduction one of the most important pre-processing steps in optical coherence tomography (oct) is reducing speckle noise, resulting from multiple scattering of tissues, which degrades the quality of oct images. materials and methods the present study focused on speckle noise reduction and edge detection techniques. statistical filters with different masks and noise variances were applied on ...

In this work, we first address the problem of simultaneous image segmentation and smoothing by approaching the Mumford-Shah paradigm from a curve evolution perspective. In particular, we let a set of deformable contours define the boundaries between regions in an image where we model the data via piecewise smooth functions and employ a gradient flow to evolve these contours. Each gradient step ...

Image registration aims to map one image to another of a same scene. It is a fundamental task in many imaging applications. Most existing image registration methods assume that the mapping transformation has a parametric form or satisfies certain regularity conditions (e.g., it is a smooth function with continuous first or higher order derivatives). They often estimate the mapping transformatio...

1.1 Introduction Low level image processing is often used to detect and localise features such as edges and corners. It is also used to correlate or match small parts of one image with parts in another. Methods for doing this have been developed for some time, However, the stochastic analysis of these algorithms have often been based upon poorly motivated stochastic models. In particular, the e...

Introduction One of the most important pre-processing steps in optical coherence tomography (OCT) is reducing speckle noise, resulting from multiple scattering of tissues, which degrades the quality of OCT images. Materials and Methods The present study focused on speckle noise reduction and edge detection techniques. Statistical filters with different masks and noise variances were applied on ...

Filtering is widely used in image and video processing for various applications among which EdgePreserving is the most popular one. Edge-preserving image smoothing has recently emerged as a valuable tool for a variety of applications such as denoising, tone mapping, non-photorealistic rendering in computer graphics and image processing. This can be achieved by a local filtering method such as b...

We present a simplified structure of 3-D adaptive LUM smoother for the impulse noise suppression in image sequences. The proposed reduced filter structure is optimized for possible hardware implementation. Introduced simplifications significantly decrease a filter complexity, however the adaptive LUM smoother based on the proposed reduced set of smoothing levels still provides excellent smoothi...

We bound the difference between the solution to the continuous Rudin–Osher–Fatemi (ROF) image smoothing model and the solutions to various finite-difference approximations to this model. These bounds apply to “typical” images, i.e., images with edges or with fractal structure. These are the first bounds on the error in numerical methods for ROF smoothing.

Contour trees have been used in geographic information systems (GIS) and medical imaging to display scalar data. Contours are only defined for continuous functions. For an image represented by discrete data, a continuous function is first defined as an interpolation of the data. Then the contour tree is defined on this continuous function. In this paper, we introduce a new concept termed monoto...