MATLAB Examples

Perform fast convolution of two matrices using the Fourier transform. A key property of the Fourier transform is that the multiplication of two Fourier transforms corresponds to the

Use fanbeam and ifanbeam to form projections from a sample image and then reconstruct the image from the projections.

Create a set of GLCMs and derive statistics from them. The example also illustrates how the statistics returned by graycoprops have a direct relationship to the original input image.

Use texture segmentation to identify regions based on their texture. The goal is to segment the dog from the bathroom floor. The segmentation is visually obvious because of the difference in

Use the Fourier transform to perform correlation, which is closely related to convolution. Correlation can be used to locate features within an image. In this context, correlation is often

Trace the border of an object in a binary image using bwtraceboundary . Then, using bwboundaries , the example traces the borders of all the objects in the image.

Compress an image using the Discrete Cosine Transform (DCT). The example computes the two-dimensional DCT of 8-by-8 blocks in an input image, discards (sets to zero) all but 10 of the 64 DCT

Measure the quality of regions of an image when compared with a reference image. The ssim function calculates the structural similarity index for each pixel in an image, based on its

Create a histogram for an image using the imhist function. An image histogram is a chart that shows the distribution of intensities in an indexed or grayscale image. The imhist function

Detect regions of texture in an image using the texture filter functions

Detect edges in an image using both the Canny edge detector and the Sobel edge detector.

Compute the Radon transform of an image, I , for a specific set of angles, theta , using the radon function. The function returns, R , in which the columns contain the Radon transform for each

Detect lines in an image using the H ough transform.

Perform quadtree decomposition on a 512-by-512 grayscale image.

Use the Radon transform to detect lines in an image. The Radon transform is closely related to a common computer vision operation known as the Hough transform. You can use the radon function to

Perform standard quality measurements on an Imatest ® edge spatial frequency response (eSFR) test chart. Measured properties include sharpness, chromatic aberration, noise,

Test image quality using ssim . The example creates images at various compression levels and then plots the quality metrics. To run this example, you must have write permission in your

Adjust the colors of an image to better match a standardized set of colors on an Imatest ® edge spatial frequency response (eSFR) test chart.

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