SuperPixelBlast Mac OS

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AImage to segment
2-D grayscale image2-D truecolor image

Image to segment, specified as a 2-D grayscale image or 2-D truecolor image. For int16 data, A must be a grayscale image. When the parameter isInputLab is true, the input image must be data type single or double.

Data Types: singledoubleint16uint8uint16

SuperPixelBlast Mac OS

Desired number of superpixels, specified as a positive integer.

Data Types: singledoubleint8int16int32int64uint8uint16uint32uint64

Name-Value Pair Arguments

Specify optional comma-separated pairs of Name,Value arguments. Name is the argument name and Value is the corresponding value. Name must appear inside quotes. You can specify several name and value pair arguments in any order as Name1,Value1,...,NameN,ValueN.

Example: B = superpixels(A,100,'NumIterations',20);

'Compactness'Shape of superpixels
10 (default) numeric scalar

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Shape of superpixels, specified as a numeric scalar. The compactness parameter of the SLIC algorithm controls the shape of superpixels. A higher value makes superpixels more regularly shaped, that is, a square. A lower value makes superpixels adhere to boundaries better, making them irregularly shaped. The allowed range is (0 Inf). Typical values for compactness are in the range [1,20].

Data Types: singledoubleint8int16int32int64uint8uint16uint32uint64

'IsInputLab'Input image data is in L*a*b* color space
false (default) true

Input image data is in the L*a*b* color space, specified as true or false.

Data Types: singledoubleint8int16int32int64uint8uint16uint32uint64logical

'Method'Algorithm used to compute superpixels
'slic0' (default) 'slic'

Algorithm used to compute superpixels, specified as one of thefollowing values. The superpixels function usestwo variations of the simple linear iterative clustering (SLIC) algorithm.

Value

Meaning

'slic0'

superpixels uses the SLIC0 algorithmto refine 'Compactness' adaptively after the firstiteration. This is the default.

'slic'

'Compactness' is constant during clustering.

Data Types: charstring

'NumIterations'Number of iterations
10 (default) positive integer

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Number of iterations used in the clustering phase of the algorithm, specified as a positive integer. For most problems, it is not necessary to adjust this parameter.

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Data Types: singledoubleint8int16int32int64uint8uint16uint32uint64