This repo relates to Rathlin deliverable D9: Encoding exemplary CAL image processing functions.
Disclaimer: This is a non-exhaustive list. Not all function will be implemented within the life-time of Rathlin (I) project. Exemplars will be implemented from selected categories.
(I: Implemented, IP: In-progress P: Planned)
#Image Arithmetic (P)
- Addition - pointwise addition: image + image (or constant)
- Subtraction - pointwise subtraction: image - image (or constant)
- Multiplication - pointwise multiplication: images * image (or constant)
- Division - pointwise division: images / image (or constant)
- Blending / Fusion - pointwise linear combination of two image
- Logical AND/NAND - pointwise logical ANDing/NANDing of two binary images
- Logical OR/NOR - pointwise logical ORing/NORing of two binary images
- Logical XOR/XNOR - pointwise logical XORing/XNORing of two binary images
- Invert / Logical NOT - pointwise inversion of a binary image
- Bitshift Operators - pointwise scaling of an image using shift operation 2^x. More efficient than division / multiplication.
- Thresholding - select pixels with given values to produce binary image
- Adaptive Thresholding - like Thresholding except choose values locally
- Contrast Stretching - spreading out graylevel distribution
- Histogram Equalisation - general method of modifying intensity distribution
- Logarithmic Operator - reducing contrast of brighter regions
- Exponential / Raise to Power Operator - enhancing contrast of brighter regions
- RGB to YUV - Color Space Converstion
- YUV to RGB - Color Space Converstion
- Scale - change image content size (Bilinear / Bicubic)
- Rotate - change image content orientation
- Reflect - flip over image contents
- Translate - change image content position
- Affine Transform - general image content linear geometric transformation
- Intensity Histogram - the image intensity distribution
- Classification - mapping from pixel values to feature or object classes
- Connected Components Labeling - grouping pixels with the same class label into regions
- Pixel Value Distribution - the number of pixels having each value
- Classified Pixels - the category of scene entity that the corresponding pixel is taken from
- Connected Componenets - the groups of pixels all of which have the same label or classification
- Dilation - grow image regions
- Erosion - shrink image regions
- Opening - structured removal of image region boundary pixels
- Closing - structured filling in of image region boundary pixels
- Hit and Miss Transform - image pattern matching and marking
- Thinning - structured erosion using image pattern matching
- Thickening - structured dilation using image pattern matching
- Skeletonization/Medial Axis Transform - finding skeletons of binary regions
- Roberts Cross Edge Detector - 2×2 gradient edge detector
- Sobel Edge Detector - 3×3 gradient edge detector (I)
- Canny Edge Detector - non-maximal suppression of local gradient magnitude
- Compass Edge Detector - 3×3 gradient edge detectors
- Zero Crossing Detector - edge detector using the Laplacian of Gaussian operator
- Line Detector - line (as distinct from edge) feature detector
- Distance Transform, maps binary images to distance from background
- Fourier Transform, maps image into spatial frequency domain
- Hough Transform, maps image into votes for specified shapes
- Wavelet Transform, maps image into spatial frequency domain -- FWT 5/3 lifting for 5 level decomposition (I)
- Motion Estimation
- Optic Flow Computation
- Histogram Computation
- Statistical Distributions
- Scene Saliency Computation
- Meanshift Tracking (I)
- Crowd Analsysis
- Person Re-Identification
- RFS tracking
- ACF pedestrian detector
#Reference read:
- http://homepages.inf.ed.ac.uk/rbf/HIPR2/wksheets.htm
- https://en.wikipedia.org/wiki/Kernel_(image_processing)
- https://en.wikipedia.org/wiki/Discrete_wavelet_transform
- https://en.wikipedia.orghttp://cvcl.mit.edu/SUNSlides/9.912-CVC-ImageAnalysis-web.pdf/wiki/Kernel_(image_processing)#Convolution
- https://en.wikipedia.org/wiki/Mean_shift
- http://www.cse.psu.edu/~rtc12/CSE598G/introMeanShift.pdf
- http://dx.doi.org/10.1109/TPAMI.2003.1195991