米ain Content

Image Filtering

Convolution and correlation, predefined and custom filters, nonlinear filtering, edge-preserving filters

Filtering is a technique for modifying or enhancing an image. For example, you can filter an image to emphasize certain features or remove other features. Image processing operations implemented with filtering include smoothing, sharpening, and edge enhancement.

Apps

Image Region Analyzer Browse and filter connected components in an image

Functions

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imfilter N-D filtering of multidimensional images
roifilt2 Filter region of interest (ROI) in image
nlfilter General sliding-neighborhood operations
imgaussfilt 2-D Gaussian filtering of images
imgaussfilt3 3-D Gaussian filtering of 3-D images
wiener2 2-D adaptive noise-removal filtering
medfilt2 2-D median filtering
medfilt3 3-D median filtering
modefilt 2-D and 3-D mode filtering
ordfilt2 2-D order-statistic filtering
stdfilt Local standard deviation of image
rangefilt 当地的形象
entropyfilt Local entropy of grayscale image
imboxfilt 2-D box filtering of images
imboxfilt3 3-D box filtering of 3-D images
fibermetric Enhance elongated or tubular structures in image using Frangi vesselness filter
maxhessiannorm 米aximum of Frobenius norm of Hessian of matrix
padarray Pad array
imbilatfilt Bilateral filtering of images with Gaussian kernels
imdiffuseest Estimate parameters for anisotropic diffusion filtering
imdiffusefilt Anisotropic diffusion filtering of images
imguidedfilter Guided filtering of images
imnlmfilt Non-local means filtering of image
burstinterpolant Create high-resolution image from set of low-resolution burst mode images
gabor Create Gabor filter or Gabor filter bank
imgaborfilt Apply Gabor filter or filter bank to 2-D image
bwareafilt Extract objects from binary image by size
bwpropfilt Extract objects from binary image using properties
integralImage Calculate 2-D integral image
integralImage3 计算三维积分图像
integralBoxFilter 2-D box filtering of integral images
integralBoxFilter3 3-D box filtering of 3-D integral images
fspecial Create predefined 2-D filter
fspecial3 Create predefined 3-D filter
convmtx2 2-D convolution matrix
freqz2 2-D frequency response
fsamp2 2-D FIR filter using frequency sampling
ftrans2 2-D FIR filter using frequency transformation
fwind1 2-D FIR filter using 1-D window method
fwind2 2-D FIR filter using 2-D window method
freqspace Frequency spacing for frequency response

Topics

Getting Started with Image Filtering in the Spatial Domain

Denoising Filtering

  • Noise Removal
    Remove image noise by using techniques such as averaging filtering, median filtering, and adaptive filtering based on local image variance.
  • Apply Gaussian Smoothing Filters to Images
    Reduce image noise by blurring the image using isotropic and anisotropic Gaussian smoothing filters of different strengths.
  • Reduce Noise in Image Gradients
    Reduce noise associated with computing image gradients so that features can be more accurately detected.

Edge-Preserving Filtering

Integral Image Domain Filtering

  • Integral Image
    Integral images are a quick way to represent images for filtering. In an integral image, the value of each pixel is the summation of the pixels above and to the left of it.
  • Apply Multiple Filters to Integral Image
    Smooth an image by different amounts by applying box filters of varying sizes to the integral image.

Frequency Domain Filtering