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wrapup.slides.printing - CS 450: Introduction to Digital...

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Unformatted text preview: CS 450: Introduction to Digital Signal and Image Processing Where Have We Been? Where Signals Come From • How audio, images, and video are stored – Sampling – Quantization • Cameras and scanners – Noise – Apertures – Tradeoffs Level Operations • Processing samples independent of others – – – – – – Brightness Contrast/Volume Quantization Thresholding Inverting/Negatives Logarithmic/exponential encoding • Automatic methods: – Histogram-based methods • Adjust brightness/contrast • Histogram equalization • Histogram specification Spatial Domain Processing • Spatial filtering / convolution • Noise reduction / blurring – Averaging filters – Median filter • Sharpening – Unsharp masking – Edge detection • Gradient • Laplacian Frequency Domain Processing • Fourier Transform – Frequency decomposition and analysis • Processing – – – – Convolution Theorem Low-pass filtering (images Æ blurring) High-pass filtering (images Æ sharpening) Band-pass filtering • Other applications – Frequency-domain multiplexing – Analysis of sampling/reconstruction Geometric Processing • Basic structure of geometric warping – Forward warping – Backwards warping • Interpolation where necessary – Types of interpolation • Global vs. local mesh-based warps – Bilinear transformations • Applications: – Resizing, rotating, correcting distortion, morphing Color • Basic properties • Color gamuts – Physical device limitations • Color models – RGB, CMYK, YIQ, HSI, HSV, Lab, … • Color image processing Compression • • Basics of information theory Coding redundancy – Entropy coders: Huffman, Arithmetic – Multiple symbol approximation: Vector Quantization • Interpixel redundancy – Repetition: RLE, LZW – Predictability: Delta Modulation, DPCM • Perceptual redundancy – Block transform encoding – JPEG. MP3 • Video – Delta frames – Motion prediction/compensation (MPEG) – Key frames What You’ve Implemented • Contrast enhancement – Histogram equalization • Image averaging or differencing • Spatial blurring (noise removal) • Spatial sharpening and edge detection • Frequency analysis • Frequency filtering – Low-pass filters – General structure for all filters • Geometric processing – Magnification, reduction, and rotation • Color processing – Color model conversion – Processing • Image compression And So Much More… • Advance image processing techniques – – – – • Computer vision – – – – – • More on filtering (See Ch. 5) Wavelets Statistical reconstruction Techniques based on partial differential equations … Segmentation (grouping the image into parts) Shape description / matching Object recognition Motion and tracking 3-D perspective projective geometry … Human vision – Understanding more about how people see – Modeling biological mechanisms and “algorithms” ...
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This note was uploaded on 03/02/2012 for the course C S 450 taught by Professor Morse,b during the Winter '08 term at BYU.

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