Data Mining Practical Machine Learning Tools and Techniques

From the Publisher: 
The accessible presentation of this book gives both a general view of the entire computer vision enterprise and also offers sufficient detail to be able to build useful applications. Users learn techniques that have proven to be useful by first-hand experience and a wide range of mathematical methods. A CD-ROM with every copy of the text contains source code for programming practice, color images, and illustrative movies. Comprehensive and up-to-date, this book includes essential topics that either reflect practical significance or are of theoretical importance. Topics are discussed in substantial and increasing depth. Application surveys describe numerous important application areas such as image based rendering and digital libraries. Many important algorithms broken down and illustrated in pseudo code. Appropriate for use by engineers as a comprehensive reference to the computer vision enterprise.

Computer vision : a modern approach = 计算机视觉 : 一种现代的方法

The Theory of Matrices. By F R. Gantmacher. Two volumes, pp. 374 and 276. 1959. (Translated from the Russian by K. A. Hirsch; Chelsea Publishing Company, New York)

http://facweb.cs.depaul.edu/research/vc/seminar/paper/cheng_2004_digital-signal-processing.pdf

A simple and effective histogram equalization approach to image enhancement

Network diffusion accurately models the relationship between structural and functional brain connectivity networks.

Computer Vision and Graphics

https://www.comm.utoronto.ca/~kostas/Publications2008/pub/32.pdf

Self-adaptive algorithm of impulsive noise reduction in color images

Towards automatic redeye effect removal

Random walk approach to image enhancement

A new approach to the problem of impulsive-noise reduction for color images is introduced. The major advantage of the technique is that it filters out the noise component while adapting itself to the local image structures. In this way the algorithm is able to eliminate strong impulsive noise while preserving edges and fine image details. As the algorithm is a fuzzy modification of the commonly used vector median operator, it is very fast and easy to implement. Our results show that the proposed method outperforms all standard algorithms for the reduction of impulsive noise in color images. © 2001 Society of Photo-Optical Instrumenta- tion Engineers. (DOI: 10.1117/1.1367347)

/pdf/on-the-reduction-of-impulsive-noise-in-multichannel-image-29gv8ku6de.pdf

Konrad Wojciechowski

Papers

Computer Vision and Graphics

Self-adaptive algorithm of impulsive noise reduction in color images

Towards automatic redeye effect removal

Random walk approach to image enhancement

On the reduction of impulsive noise in multichannel image processing