IMAGE PROCESSING with MATLAB

by T. Kendall



Image Processing Toolbox provides a comprehensive set of reference-standard algorithms and graphical tools for image processing, analysis, visualization, and algorithm development. You can perform image enhancement, image deblurring, feature detection, noise reduction, image segmentation, spatial transformations, and image registration. Many toolbox functions are multithreaded to take advantage of multicore and multiprocessor computers. Image Processing Toolbox supports a diverse set of image types, including high dynamic range, gigapixel resolution, ICC-compliant color, and tomographic. Graphical tools let you explore an image, examine a region of pixels, adjust the contrast, create contours or histograms, and manipulate regions of interest (ROIs). With toolbox algorithms you can restore degraded images, detect and measure features, analyze shapes and textures, and adjust color balance. The more importan features are de next:

• Image enhancement, filtering, and deblurring
• Image analysis, including segmentation, morphology, feature extraction, and measurement
• Spatial transformations and intensity-based image registration methods
• Image transforms, including FFT, DCT, Radon, and fan-beam projection
• Workflows for processing, displaying, and navigating arbitrarily large images
• Interactive tools, including ROI selections, histograms, and distance measurements
• DICOM file import and export