Digital Image Processing: Image Enhancement - Duong Anh Duc presents about Image Enhancement; Point Operations; Image Negative; Contrast Stretching; Compression of Dynamic Range; Image Averaging for noise reduction; Some Averaging Filters; Some Typical Histograms. | 5/14/2020 4:35:03 AM Duong Anh Duc - Digital Image Processing Digital Image Processing Image Enhancement 5/14/2020 4:35:03 AM Duong Anh Duc - Digital Image Processing Image Enhancement To process an image so that output is “visually better” than the input, for a specific application. Enhancement is therefore, very much dependent on the particular problem/image at hand. Enhancement can be done in either: Spatial domain: operate on the original image g(m,n) = T[f(m,n)] Frequency domain: operate on the DFT of the original image G(u,v) = T[F(u,v)], where F(u,v) = F[f(m,n)], and G(u,v) = F [g(m,n)], 5/14/2020 4:35:03 AM Duong Anh Duc - Digital Image Processing Image Enhancement Techniques Point Operations Mask Operations Transform Operations Coloring Operations Image Negative Contrast Stretching Compression of dynamic range Graylevel slicing Image Subtraction Image Averaging Histogram operations Smoothing operations Median Filtering Sharpening operations Derivative operations . | 5/14/2020 5:31:14 AM Duong Anh Duc - Digital Image Processing Digital Image Processing Image Enhancement 5/14/2020 5:31:14 AM Duong Anh Duc - Digital Image Processing Image Enhancement To process an image so that output is “visually better” than the input, for a specific application. Enhancement is therefore, very much dependent on the particular problem/image at hand. Enhancement can be done in either: Spatial domain: operate on the original image g(m,n) = T[f(m,n)] Frequency domain: operate on the DFT of the original image G(u,v) = T[F(u,v)], where F(u,v) = F[f(m,n)], and G(u,v) = F [g(m,n)], 5/14/2020 5:31:14 AM Duong Anh Duc - Digital Image Processing Image Enhancement Techniques Point Operations Mask Operations Transform Operations Coloring Operations Image Negative Contrast Stretching Compression of dynamic range Graylevel slicing Image Subtraction Image Averaging Histogram operations Smoothing operations Median Filtering Sharpening operations Derivative operations Histogram operations Low pass Filtering Hi pass Filtering Band pass Filtering Homomorphic Filtering Histogram operations False Coloring Full color Processing 5/14/2020 5:31:14 AM Duong Anh Duc - Digital Image Processing Point Operations Output pixel value g(m, n) at pixel (m, n) depends only on the input pixel value at f(m, n) at (m, n) (and not on the neighboring pixel values). We normally write s = T(r), where s is the output pixel value and r is the input pixel value. T is any increasing function that maps [0,1] into [0,1]. 5/14/2020 5:31:14 AM Duong Anh Duc - Digital Image Processing Image Negative T(r) = s = L-1-r, L: max grayvalue 5/14/2020 5:31:14 AM Duong Anh Duc - Digital Image Processing Negative Image 5/14/2020 5:31:14 AM Duong Anh Duc - Digital Image Processing Contrast Stretching Increase the dynamic range of grayvalues in the input image. Suppose you are interested in stretching the input intensity values in the interval [r1, r2]: Note that (r1- r2) < (s1-
