Chapter 3. Intensity Transformations and Spatial Filtering ❖Two principal categories of spatial processing are intensity transformations and spatial filtering. ➢ Intensity transformations operate on single pixels of an image for tasks such as contrast manipulation and image thresholding. ➢ Spatial filtering performs operations on the neighborhood of every pixel in an image. ➢ Examples of spatial filtering include image smoothing and sharpening. Rafael C. Gonzalez, Richard E. Woods, “Digital image processing,” Pearson (2018). 2 Chapter 3. Intensity Transformations and Spatial Filtering 1. Background 2. Some Basic Intensity Transformation Functions 3. Histogram Processing 4. Fundamentals of Spatial Filtering 5. Smoothing (Lowpass) Spatial Filters 6. Sharpening (Highpass) Spatial Filters 7. Highpass, Bandreject, and Bandpass Filters from Lowpass Filters 8. Combining Spatial Enhancement Methods Rafael C. Gonzalez, Richard E. Woods, “Digital image processing,” Pearson (2018). 3 1. Background ❖The Basics of Intensity Transformations and Spatial Filtering ➢ The spatial domain processes are based on the expression where f(x, y) is an input image, g(x, y) is the output image, and T is an operator on f defined over a neighborhood of point (x, y). A 3x3 neighborhood about a point (x0, y0) in an image. The neighborhood is moved from pixel to pixel in the image to generate an output image. Rafael C. Gonzalez, Richard E. Woods, “Digital image processing,” Pearson (2018). 4 1. Background ❖The Basics of Intensity Transformations and Spatial Filtering ➢ intensity (also called a gray-level, or mapping) transformation function Intensity transformation functions. (a) Contrast stretching function. (b) Thresholding function. Rafael C. Gonzalez, Richard E. Woods, “Digital image processing,” Pearson (2018). 5 Chapter 3. Intensity Transformations and Spatial Filtering 1. Background 2. Some Basic Intensity Transformation Functions 3. Histogram Processing 4. Fundamentals of

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