Contrast enhancement plays a crucial role in the field of image processing. Histogram equalization is a simple and automatic method for contrast enhancement. Conventional contrast-enhancement techniques, such as histogram specification and contrast stretching, require manual parameters to achieve satisfactory results. To automatically produce enhanced results for low-contrast images, a new hist...

Perceptual popout is defined by both feature similarity and local feature contrast. We identify these two measures with attraction and repulsion, and unify the dual processes of association by attraction and segregation by repulsion in a single grouping framework. We generalize normalized cuts to multi-way partitioning with these dual measures. We expand graph partitioning approaches to weight ...

The problem of grouping Printed Circuit Board (PCB) components to minimize the total component and PCB loading cost subject to a capacity constraint on the number of types of components per group is formulated as an integer linear programming problem. The problem is shown to be NP-complete. Characteristics of the solution are outlined and a heuristic algorithm is discussed. For the case in whic...

Grouping of a set of Secondary Surveillance Radar (SSR) Mode S stations into functional entities called clusters has significant operational facets; it calls for a constrained optimization, an important significant constraint being the scarcity of Interrogation Identifier (II) codes. This clustering problem can be approached by two ways, i.e., integer programming methods and heuristic approache...

We propose an algorithm to distinguish 3D+t images of healthy from diseased subjects by solving logistic regression based on cardinality constrained, group sparsity. This method reduces the risk of overfitting by providing an elegant solution to identifying anatomical regions most impacted by disease. It also ensures that consistent identification across the time series by grouping each image f...

In this paper, we propose a level set formulation to deal with the segmentation and registration of the left ventricle in Magnetic Resonance (MR) images. Our approach is based on the integration of visual information, anatomical constraints and a flexible shape-driven cardiac model. The visual information is expressed through an intensity-based grouping module. The anatomical constraint account...

A model for perceptual grouping based on measurements of spatial correlations is proposed and tested. Gestalt-like grouping experiments were performed to study and quantify the effect of element similarity (shape, luminance) and proximity. Observers reported the horizontal or vertical organization of stimuli with proximity and similarity providing conflicting grouping cues. Proximity grouping w...

Lifted probabilistic inference algorithms exploit regularities in the structure of graphical models to perform inference more efficiently. More specifically, they identify groups of interchangeable variables and perform inference once for each group, as opposed to once for each variable. The groups are defined by means of constraints, so the flexibility of the grouping is determined by the expr...

Given an undirected graph G = (V,E) with weights on the edges, the maxbisection problem (MBP) is to find a partition of the vertex set V into two subsets V1 and V2 of equal cardinality such that the sum of the weights of the edges crossing V1 and V2 is maximized. Relaxing the equal cardinality constraint leads to the maxcut problem (MCP). In this work, we present a memetic algorithm for MBP whi...

EVOLUTIONARY PSYCHOLOGY OFTEN does not sufficiently document the innate constraint and domain specificity required for strong adaptationist argument. We develop these criteria within the domain of music. First, we advocate combining computational, developmental, cross-cultural, and neuroscience research to address the ways in which a domain is innately constrained. Candidate constraints in musi...