Read an image into the workspace, adjust the contrast in the image, and then write the adjusted image to a file.
Use Wiener deconvolution to deblur images. Wiener deconvolution can be useful when the point-spread function and noise level are either known or estimated.
Use the Lucy-Richardson algorithm to deblur images. It can be used effectively when the point-spread function PSF (blurring operator) is known, but little or no information is available
Use regularized deconvolution to deblur images. Regularized deconvolution can be used effectively when constraints are applied on the recovered image (e.g., smoothness) and limited
Train a denoising convolutional neural network (DnCNN), then use the network to reduce JPEG compression artifacts in an image.
Train a U-Net convolutional neural network to perform semantic segmentation of a multispectral image with seven channels: three color channels, three near-infrared channels, and a mask.
Several ways to get the handle to the image displayed in a figure window, referred to as the target image . This can be useful when creating apps with the modular interactive tools.
Correct nonuniform illumination in an image to make it easy to identify individual grains of rice in the image. You can then learn about the characteristics of the grains and easily compute
Several image enhancement approaches. Three functions are particularly suitable for contrast enhancement: imadjust , histeq , and adapthisteq . This example compares their use for
Some basic image composition and enhancement techniques for use with multispectral data. It is often necessary to enhance multispectral radiance or reflectance data to create an image
Our eyes are very good at judging what is white under different lighting conditions. Digital cameras, however, without some kind of adjustment, can easily capture unrealistic images with a
Perform a simple affine transformation called a translation. In a translation, you shift an image in coordinate space by adding a specified value to the x- and y-coordinates. (You can also
Use phase correlation as a preliminary step for automatic image registration. In this process, you perform phase correlation, using imregcorr , and then pass the result of that
Use spatial referencing objects to understand the spatial relationship between two images in image registration and display them effectively. This example brings one of the images,
Specify the fill values used by imwarp when it performs a geometric transformation. When you perform a transformation, there are often pixels in the output image that are not part of the
You can combine multiple transformations into a single matrix using matrix multiplication. The order of the matrix multiplication matters.
Rotate an image using the imrotate function. When you rotate an image, you specify the image to be rotated and the rotation angle, in degrees. If you specify a positive rotation angle, the
Apply different Gaussian smoothing filters to images using imgaussfilt . Gaussian smoothing filters are commonly used to reduce noise.
Deblur an image using blind deconvolution. The example illustrates the iterative nature of this operation, making two passes at deblurring the image using optional parameters.
Create filters using the fspecial function that can be used with imfilter. The fspecial function produces several kinds of predefined filters, in the form of correlation kernels. This
Use histogram equalization to adjust the contrast of a grayscale image. The original image has low contrast, with most pixel values in the middle of the intensity range. histeq produces an
Increase the contrast in a low-contrast grayscale image by remapping the data values to fill the entire available intensity range [0, 255].
Plot the transformation curve for histogram equalization. histeq can return a 1-by-256 vector that shows, for each possible input value, the resulting output value. (The values in this
Specify gamma when adjusting contrast with the imadjust function. By default, imadjust uses a gamma value of 1, which means that it uses a linear mapping between intensity values in the
Use a guided filter to smooth an image, reducing noise, while preserving edges. The example uses two pictures of the same scene, one taken with a flash and the other without a flash. The version
Remove salt and pepper noise from an image using an averaging filter and a median filter to allow comparison of the results. These two types of filtering both set the value of the output pixel to
Use masked filtering to increase the contrast of a specific region of an image.
Filter a region of interest (ROI), using the roifilt2 function to specify the filter. roifilt2 enables you to specify your own function to operate on the ROI. This example uses the imadjust
Apply multiple box filters of varying sizes to an image using integral image filtering. Integral image is a useful image representation from which local image sums can be computed rapidly. A
Work with thermal images, demonstrating a simple segmentation. Thermal images are obtained from thermographic cameras, which detect radiation in the infrared range of the
Dilate an image using the imdilate function. The morphological dilation operation expands or thickens foreground objects in an image.
Demonstrates how to reduce noise associated with computing image gradients. Image gradients are used to highlight interesting features in images and are used in many feature detection
Filter a 2-D grayscale image with a 5-by-5 filter containing equal weights (often called an averaging filter) using imfilter . The example also shows how to filter an truecolor (RGB) image
Find the perimeter pixels in a binary image using the bwperim function.
Specify contast adjustment limits as a range using the imadjust function. This example decreases the contrast of an image by narrowing the range of the data.
Read the three visible color channels of the LANDSAT image of the Little Colorado River.
Perform decorrelation stretching to three color bands of an image. A color band scatterplot of the images shows how the bands are decorrelated and equalized.
Automatically align two images that differ by a rotation and a scale change. It closely parallels another example titled Find Image Rotation and Scale. Instead of using a manual approach to
Use imregister, imregtform and imwarp to automatically align two volumetric datasets: a CT image and a T1 weighted MR image collected from the same patient at different times. Unlike some
Align or register two images that differ by a rotation and a scale change. You can use fitgeotrans to find the rotation angle and scale factor after manually picking corresponding points. You
Use imregister to automatically align two magnetic resonance (MRI) images to a common coordinate system using intensity-based image registration. Unlike some other techniques, it does
Register an aerial photo to an orthophoto. Two images of the same scene can only be compared directly if they are in the same coordinate system. Image registration is the process of
Identify different colors in fabric by analyzing the L*a*b* colorspace. The fabric image was acquired using the Image Acquisition Toolbox™.
Use texture segmentation to identify regions based on their texture. Your goal is to segment two kinds of fabric in an image using texture filters.
Detect cars in a video of traffic. You can use Image Processing Toolbox™ to visualize and analyze videos or image sequences. This example uses VideoReader (MATLAB®), implay , and other Image
Segment colors in an automated fashion using the L*a*b* color space and K-means clustering.
Use watershed segmentation to separate touching objects in an image. The watershed transform is often applied to this problem. The watershed transform finds "catchment basins" and
Detect a cell using edge detection and basic morphology. An object can be easily detected in an image if the object has sufficient contrast from the background. In this example, the cells are
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
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
Write image data from the MATLAB workspace to a file in one of the supported graphics file formats using the imwrite function.
To read image data from a graphics file into the MATLAB workspace using the imread function.
Use color space conversion to determine if an L*a*b* value is in the RGB gamut. The set of colors that can be represented using a particular color space is called its gamut . Some L*a*b* color
Read multiple images from a single graphics file. Some graphics file formats allow you to store multiple images. You can read these images using format-specific parameters with imread . By
When you use rgb2ind or imapprox to reduce the number of colors in an image, the resulting image might look inferior to the original, because some of the colors are lost. rgb2ind and imapprox
Creates a simple truecolor image and then separates the color channels (planes). The example displays each color channel and the original image.
Measure the radius of a roll of tape, which is partially obscured by the tape dispenser. Utilize imfindcircles to accomplish this task.
Measure the angle and point of intersection between two beams using bwtraceboundary , which is a boundary tracing routine. A common task in machine vision applications is hands-free
Use imfindcircles to automatically detect circles or circular objects in an image. It also shows the use of viscircles to visualize the detected circles.
Calculate the size distribution of snowflakes in an image by using granulometry. Granulometry determines the size distribution of objects in an image without explicitly segmenting
Classify objects based on their roundness using bwboundaries , a boundary tracing routine.
Calculate the length of a pendulum in motion. You can capture images in a time series with the Image Acquisition Toolbox™ and analyze them with the Image Processing Toolbox™.
Explore a conformal mapping. Geometric image transformations are useful in understanding a conformal mapping that is important in fluid-flow problems, and the mapping itself can be used
Construct a tform struct that represents a simple shear transformation and then applies it to an image. We explore how the transformation affects straight lines and circles, and then use it
Explore a volume of data by extracting slices through a three-dimensional MRI data set using imtransform and tformarray functions.
Use blockproc to compute statistics from large images and then use that information to more accurately process the images blockwise. The blockproc function is well suited for applying an