This part covers the most essential image processing techniques for image visualisation, quantitative analysis and thematic information extraction for remote sensing applications. A series of chapters introduce topics with increasing complexity from basic visualisation algorithms, which can be easily used to improve your digital camera pictures, to more complicated multi-dimensional transform-based techniques.
Digital image processing can improve image visual quality, selectively enhance and highlight particular image features and classify, identify and extract spectral and spatial patterns representing different thematic information from images. It can also arbitrarily change image geometry and illumination conditions to give different views of the same image. Importantly, image processing cannot increase information from the original image data, although it can indeed optimise the visualisation for us to see more from the enhanced images than from the original.
For real applications our considered opinion, based on years of experience, is that simplicity is beautiful. Image processing does not follow the well-established physical law of energy conservation. As shown in Fig. P.1, often the results produced using very simple processing techniques in the first 10 minutes of your project may actually represent 90% of the job done! This should not encourage you to abandon this book after the first three chapters since it is the remaining 10% that you achieve during the 90% of your time that will serve the highest level objectives of your project. The key point is that thematic image processing should be application driven, whereas our learning is usually technique driven.
