Image-processing specialists use concepts and tools to solve practical problems. Some of these tools are linear, while others are nonlinear. The specialist develops a recipe for solving this problem by combining various tools in different sequences. To solve a given problem, one recipe may call for image preprocessing followed by feature extraction and finally object recognition. Another recipe may skip the preprocessing and feature extraction, and instead perform the recognition directly using a matched filter on the raw image data. Once a recipe is selected, it may require a number of parameters, that, depending on the practical constraint, may need to be optimized to obtain the best result given the image quality, dimension, or content.
In this Field Guide, we introduce a set of basic imageprocessing concepts and tools: image transforms and spatial domain filtering; point processing techniques; the Fourier transform and its properties and applications; image morphology; the wavelet transform; and image compression and data redundancy techniques. From these discussions, readers can gain an understanding of how to apply these various tools to image-processing problems. However, true mastery is only gained when one has an opportunity to work with some of these tools.
We acknowledge our gratitude to our family members and parents for giving us the opportunity to work on this book. In particular, Dr. Iftekharuddin would like thank Tasnim and Labib for their constant support, and parents Muhammad Azharuddin and Khaleda Khanam for their encouragement; Dr. Awwal would like to thank Syeda, Ibrahim, and Maryam for their constant support, and parents Mohammad Awwal and Saleha Khatoon for their encouragement.
Old Dominion University
Lawrence Livermore National Laboratory