public SIFT(
	int nFeatures = 0,
	int nOctaveLayers = 3,
	double contrastThreshold = 0.04,
	double edgeThreshold = 10,
	double sigma = 1.6
)

Public Sub New ( 
	Optional nFeatures As Integer = 0,
	Optional nOctaveLayers As Integer = 3,
	Optional contrastThreshold As Double = 0.04,
	Optional edgeThreshold As Double = 10,
	Optional sigma As Double = 1.6
)

public:
SIFT(
	int nFeatures = 0, 
	int nOctaveLayers = 3, 
	double contrastThreshold = 0.04, 
	double edgeThreshold = 10, 
	double sigma = 1.6
)

new : 
        ?nFeatures : int * 
        ?nOctaveLayers : int * 
        ?contrastThreshold : float * 
        ?edgeThreshold : float * 
        ?sigma : float 
(* Defaults:
        let _nFeatures = defaultArg nFeatures 0
        let _nOctaveLayers = defaultArg nOctaveLayers 3
        let _contrastThreshold = defaultArg contrastThreshold 0.04
        let _edgeThreshold = defaultArg edgeThreshold 10
        let _sigma = defaultArg sigma 1.6
*)
-> SIFT

Parameters

nFeatures (Optional)

Type: SystemInt32
The number of best features to retain. The features are ranked by their scores (measured in SIFT algorithm as the local contrast)

nOctaveLayers (Optional)

Type: SystemInt32
The number of layers in each octave. 3 is the value used in D. Lowe paper. The number of octaves is computed automatically from the image resolution.

contrastThreshold (Optional)

Type: SystemDouble
The contrast threshold used to filter out weak features in semi-uniform (low-contrast) regions. The larger the threshold, the less features are produced by the detector.

edgeThreshold (Optional)

Type: SystemDouble
The threshold used to filter out edge-like features. Note that the its meaning is different from the contrastThreshold, i.e. the larger the edgeThreshold, the less features are filtered out (more features are retained).

sigma (Optional)

Type: SystemDouble
The sigma of the Gaussian applied to the input image at the octave #0. If your image is captured with a weak camera with soft lenses, you might want to reduce the number.

Reference