SI Computational Intelligence in Image Processing 2014, http://www.hindawi.com/journals/mpe/si/164921/cfp/, NN

Vision in general and images in particular have always played an essential role in human life&#046; In the past they were, today they are, and in the future they will continue to be one of our most important information carriers&#046; Recent advances in digital imaging and computer hardware technology have led to an explosion in the use of digital images in a variety of scientific and engineering applications&#046; These applications result from the interaction between fundamental scientific research on the one hand, and the development of new and high&#8211;standard technology on the other hand&#046;<br>Computational intelligence has emerged as powerful tools for information processing, decision making, and knowledge management&#046; The techniques of computational intelligence have been successfully developed in areas such as neural networks, fuzzy systems, and evolutionary algorithms&#046; It is predictable that in the near future computational intelligence will play a more and more important role in tackling several engineering problems&#046;<br>Image processing is a very important research area&#046; Classical image processing methods often face great difficulties while dealing with images containing noise and distortions&#046; Under such conditions, the use of computational intelligence approaches has been recently extended to address challenging real&#8211;world image processing problems&#046; This special issue aims to provide a collection of high quality research articles that address broad challenges in both theoretical and application aspects of computational intelligence in image processing&#046; We invite colleagues to contribute original research articles as well as review articles that will stimulate the continuing effort on the application of computational intelligence approaches to solve image processing problems&#046; Potential topics include, but are not limited to:<br>The use of computational intelligence techniques such as:<br>Neural networks<br>Fuzzy logic<br>Rough sets<br>Metaheuristics (evolutionary algorithms, simulated annealing, tabu search, ant colony optimization, particle swarm optimization, harmony search, bee colony optimization, etc&#046;)<br>Expert systems<br>In/for:<br>Coding and compression<br>Sampling and interpolation<br>Quantization and halftoning<br>Quality assessment<br>Filtering and enhancement<br>Morphology<br>Edge detection and segmentation<br>Feature extraction<br>Indexing and retrieval<br>