|Compute 2-D discrete convolution of two input matrices|
|Two-dimensional discrete Fourier transform|
|Two–dimensional inverse discrete Fourier transform|
|Compute 2-D discrete cosine transform|
|Compute 2-D inverse discrete cosine transform|
|Remove motion artifacts by deinterlacing input video signal|
|Perform Gaussian pyramid decomposition|
|2-D Convolution||Compute 2-D discrete convolution of two input matrices|
|2-D FFT||Compute two-dimensional fast Fourier transform of input|
|2-D IFFT||2-D Inverse fast Fourier transform of input|
|2-D DCT||Compute 2-D discrete cosine transform (DCT)|
|2-D IDCT||Compute 2-D inverse discrete cosine transform (IDCT)|
|2-D FIR Filter||Perform 2-D FIR filtering on input matrix|
|Contrast Adjustment||Adjust image contrast by linearly scaling pixel values|
|Deinterlacing||Remove motion artifacts by deinterlacing input video signal|
|Edge Detection||Find edges of objects in images using Sobel, Prewitt, Roberts, or Canny method|
|Histogram Equalization||Enhance contrast of images using histogram equalization|
|Median Filter||Perform 2-D median filtering|
|Hough Transform||Find lines in images|
|Hough Lines||Find Cartesian coordinates of lines described by rho and theta pairs|
|Gaussian Pyramid||Perform Gaussian pyramid decomposition|
This example shows you how to modify the contrast in two intensity images using the Contrast Adjustment and Histogram Equalization blocks.
This example shows you how to modify the contrast in color images using the Histogram Equalization block.
Median filtering is a common image enhancement technique for removing salt and pepper noise.
To sharpen a color image, you need to make the luma intensity transitions more acute, while preserving the color information of the image.
Find lines within images
Find the edges of rice grains in an intensity image