Parallel Image Processing

This book developed out of a series of publications in the area of image processing with massively parallel algorithms. The topic of image processing is a particularly promising area for the use of synchronous massively parallel or data-parallel compu­ ter systems which work according to the SIMD principle (single instruction, multiple data). While the era of large SIMD super-computers has passed, SIMD systems have come back as dedicated vision subsystems and will soon be found even in embedded systems. In comparison to conventional sequential implementations of basic image opera­ tions, this book illustrates the intrinsic parallelism which is almost always present in image processing. By utilising parallel algorithms it is even possible to illustrate oper­ ations in a simpler and easier to understand way than for the sequential case. The presentation method chosen for this book assumes that short, terse excerpts of program code will significantly enhance the understanding of the material, e.g. of image operations, while longer listings are more likely to distract from the topic. For this reason, each chapter will not only define and explain the central image processing algorithms with the help of examples, but will also give an excerpt of a massively par­ allel program. For image processing this means that at least virtually there should be one processor available for each pixel. The mapping onto a smaller number of exist­ by compiler, and as of ing real processors is done transparently the such is not interest here. This book serves as a general introduction to the area of image processing as well as to data-parallel processing. It covers a number of standard algorithms in image processing and describes their parallel implementation in a practical "hands-on" approach: Each algorithm is accompanied by numerous diagrams and program source code. Combining text, graphics, and programs is a new approach in presenting the subject matter, which will help students to better grasp the concepts - irrespective of the programming language used. The programming language chosen for all examples is a structured parallel programming language which is ideal for educational purposes. It has a number of advantages over C, and since all image processing tasks are inherently parallel, using a parallel language for presentation actually simplifies the subject matter, resulting in shorter source codes and better understanding. Sample programs and a free compiler are available on the Web.

This book introduces the area of image processing and data-parallel processing. It covers a number of standard algorithms in image processing and describes their parallel implementation. The programming language chosen for all examples is a structured parallel programming language which is ideal for educational purposes. It has a number of advantages over C, and since all image processing tasks are inherently parallel, using a parallel language for presentation actually simplifies the subject matter. This results in shorter source codes and a better understanding. Sample programs and a free compiler are available on an accompanying Web site.

Front Matter....Pages I-IX Introduction....Pages 1-6 Point Operators....Pages 7-17 Local Operators....Pages 19-26 Edge Detection....Pages 27-32 Skeletonizing....Pages 33-49 Morphological Operators....Pages 51-58 Segmentation....Pages 59-63 Corner Detection....Pages 65-81 Hough Transform....Pages 83-97 Fourier Transform....Pages 99-119 Texture Recognition....Pages 121-130 Stereo Image Processing....Pages 131-143 Analysis of Image Sequences....Pages 145-168 Back Matter....Pages 169-203 Introduction Point Operators Local Operators Edge Detection Skeletonizing Morphological Operators Segmentation Corner Detection Hough Transform Fourier Transform Texture Recognition Stereo Image Processing Analysis of Image Sequences Appendix: Parallaxis Parallel Programming Language; Parallaxis-III Syntax; Programming Tools; Vision Library; References Index.