In this paper, we present a general theory of adaptive mathematical morphology (AMM) in the Euclidean space. The proposed theory preserves the notion of a structuring element, whi...
The estimation of high-dimensional probability density functions (PDFs) is not an easy task for many image processing applications. The linear models assumed by widely used transf...
Many applications commonly found in digital signal processing and image processing applications can be represented by data-flow graphs (DFGs). In our previous work, we proposed a ...
Capturing dependencies in images in an unsupervised manner is important for many image processing applications. We propose a new method for capturing nonlinear dependencies in ima...
Online adaptation is a key requirement for image processing applications when used in dynamic environments. In contrast to batch learning, where retraining is required each time a...
Image processing applications (IPA) requirements can be best met by using the distributed environment. The authors had developed an environment over a network of VAX/VMS and Unix f...
We demonstrate the use of a "smart camera" to accelerate two very different image processing applications. The smart camera consists of a high quality video camera and f...
- Most image processing applications are computationally intensive and data intensive. Reconfigurable hardware boards provide a convenient and flexible solution to speed up these a...
In this paper, an interactive system for the development of Image Processing applications is described. This system is intended to provide some assistance to Image Processing exper...
Markov Random Fields are widely used in many image processing applications. Recently the shortcomings of some of the simpler forms of these models have become apparent, and models ...