Image transformations and filters

A part of the CVonline computer vision resource summarizing the different image-to-image transformations structures commonly encountered in computer vision and image processing.

1. Image enhancement

   1. Artistic effects

   2. Brightness adjustment

   3. Contrast adjustment

      1. Histogram equalization

      2. Contrast stretching

   4. Edge sharpening

   5. Histogram equalization/Adaptive histogram equalization

   6. Quantile normalization

   7. Saturation adjustment

   8. Upsampling

2. Distance and skeleton

• 1. Distance transform

  2. Eccentricity transform

  3. Laplacian eigenspace

  4. Medial axis

  5. Morphological skeletons

  6. Topological skeletons

  7. Local symmetry

  8. Principal component encoding

  9. Shock (mechanics)

     1. Shock filter, Shock tree, Shock graph

     2. Shock response spectrum

  10. Smoothed local symmetry

3. Geometric transformations

• 1. Euclidean: Rotation, Translation, Reflection

  2. Subsampling, Interpolation, zooming

  3. Rectification

  4. Image scaling, Shear transformation, Affine transformation, Projective transformation

  5. Image warping

4. Global transforms

• 1. Discrete cosine/Discrete sine transforms

  2. Fourier transform

     1. Frequency domain filtering

     2. Homomorphic filtering

     3. Non-uniform Fourier transform

     4. Fourier optics

     5. Log-polar/Polar Fourier transform

  3. Haar transform

  4. Hartley transform

  5. Hadamard/Walsh transform

  6. Histogram transformation

• • 1. Histogram equalization

    2. Adaptive histogram equalization

    3. Image histogram

    4. Color histogram

• 7. Karhunen-Loeve transform

  8. Radon transform, Mojette transform

  9. Ridgelet transform

  10. Slant transform

  11. Modified wavefield transform

  12. Trace transform

  13. Wavelet transform

5. Image and Video compression

• 1. Adaptive coding

  2. Arithmetic coding

  3. Block Truncation Coding, Gif, TIFF, Lempel–Ziv–Welch, Huffman coding

  4. Color image compression

  5. Differential Pulse Code Modulation (DPCM)

  6. Feature extraction from compressed images

  7. Fractal compression

  8. Hierarchical compression

  9. Lossy compression

  10. Lossless compression

  11. Image quality evaluation/comparison

  12. JPEG

  13. PNG

  14. Model-based coding

  15. Motion coding, Video coding

  16. MPEG

  17. Predictive methods

  18. Stereo image compression

  19. Vector quantization

  20. Wavelet/Scalar quantization

6. Image intensity normalization

• 1. Normalized RGB

  2. Retinex

     1. Multi-scale Retinex

     2. Single-scale Retinex

  3. Self-quotient image

  4. Weber Law descriptor

7. Image stabilization

8. Local operator transforms

• 1. Adaptive filtering

  2. Composite filtering

  3. Convolution

     1. Normalized convolution

     2. Separable templates

        1. Gaussian blur

  4. Difference of Gaussians

  5. Differentiation filtering

  6. Frequency filtering

• • 1. High-pass filter

    2. Low-pass filter

    3. Matched filter

• 7. Image noise reduction and restoration

• • 1. Adaptive smoothing

    2. Anisotropic filtering

    3. Anscombe transform

    4. Moving average smoothing

    5. Bayesian filtering

    6. Bilateral filtering

    7. Brightness distortion correction

       1. Helicon filter

    8. Conservative smoothing

    9. Crimmins smoothing

    10. Deconvolution

    11. Diffusion methods

• • • 1. Diffusion equation

      2. Anisotropic diffusion

• • 12. Edge-preserving smoothing

    13. Gaussian smoothing

    14. Global filters

• • • 1. Curvature (mean, gaussian) regularized filtering

      2. Tikhonov regularization

      3. Maximum entropy methods

• • 15. Kalman filter based noise reduction

    16. Alpha beta filter

    17. Phase-locked loop

    18. Kuwahara filter

    19. Bayer filter

    20. Lee's local statistics filter

    21. Local nonlinear image restoration

    22. Median filtering

    23. Median flow filtering

    24. Median least variance/Median coefficient of variation filters

    25. Markov chain Monte Carlo

    26. Multispectral images

• • • 1. Multichannel/Multispectral filtering

• • 27. Exponential smoothing

    28. Partial Differential Equations (PDEs), Diffusion methods

• • • 1. Geometric flow, Ricci flow

      2. Tangential diffusion

• • 29. Order statistic filters

    30. Savitzky–Golay smoothing filter

    31. Scale space filter

    32. Spline smoothing

    33. Temporal averaging

    34. Wiener filter

9. Morphological transformations

• 1. Binary mathematical morphology

  2. Boolean convolution

  3. Conditional dilation

  4. Dilate/Erode transformation

  5. Fuzzy morphology/Soft morphology

  6. Grayscale morphology

     1. Grayscale dilation, Grayscale erosion, Umbra dilation, Umbra erosion

     2. Greylevel, Greyscale morphological opening, closing

        1. Opening

        2. Closing

  7. Morphological smoothing

  8. Morphological gradient

  9. Morphological laplacian

  10. Hit-or-miss transform

  11. Morphological segmentation

  12. Morphological opening, Morphological closing

  13. Region-filling, Propagation

  14. Thinning, Thickening

  15. Top-hat transform

  16. Watershed transform

10. Pixel classification

• 1. Color, Multispectral based

  2. Curvature, Shape based

  3. Edge type labeling

  4. Intensity based

  5. Shadow type labeling

  6. Texture based

11. Point binary image operator transforms

• 1. Image arithmetic

     1. Image operators: Addition

     2. Image operators: Bitshift

     3. Image operators: Blending

     4. Image operators: Division

     5. Image operators: Multiplication

     6. Image operators: Subtraction

  2. Binary operations

• • 1. Image operators: AND/NAND

    2. Image operators: NOT/INVERT

    3. Image operators: OR/NOR

    4. Image operators: XOR/XNOR

12. Point unary image operator transforms

• 1. Clipping

  2. Pixel logarithm and exponential

  3. Gamma correction

  4. Ordinal transformation

  5. Thresholding

     1. Adaptive thresholding

     2. Edge image thresholding

     3. Balanced histogram thresholding

     4. Multiband thresholding

     5. Quantization techniques

     6. Threshold selection

13. Segmentation, Grouping transforms

• 1. Property basis

     1. CAMshift (Continuously Adaptive Mean Shift)

     2. Chroma keying

     3. Intensity based segmentation (See Region detection -> thresholding)

     4. Motion based segmentation (See Motion field->Region segmentation/decomposition)

     5. Surface shape based segmentation (See Curvature-based surface patch detection)

     6. Texture based segmentation (See Texture-based region segmentation)

  2. Structures

• • 1. Curve segmentation (See Boundary/Line/Curve segmentation)

    2. Blob detection

    3. Surface segmentation (See Surface segmentation from 2 1/2D or 3D data)

    4. Volume segmentation

• 3. Technologies

• • 1. Clustering based segmentation

    2. Connected components/Blob extraction

    3. Model based feature detection/Model based segmentation

    4. Minimum description length

    5. Region growing based segmentation

    6. Relaxation labeling

    7. Rule-based/Expert-system based segmentation

    8. Thresholding based segmentation