Distance functions¶
This module supports functions to calculate the distance between two vectors.
chebychev¶
-
pysptools.distance.
chebyshev
(s1, s2)¶ Computes the chebychev distance between two vector.
- Parameters:
- s1: numpy array
- The first vector.
- s2: numpy array
- The second vector.
- Returns: float
- Chebychev distance between s1 and s2.
NormXCorr¶
-
pysptools.distance.
NormXCorr
(s1, s2)¶ Computes the normalized cross correlation distance between two vector.
- Parameters:
- s1: numpy array
- The first vector.
- s2: numpy array
- The second vector.
- Returns: float
- NormXCorr distance between s1 and s2, dist is between [-1, 1]. A value of one indicate a perfect match.
SAM¶
-
pysptools.distance.
SAM
(s1, s2)¶ Computes the spectral angle mapper between two vectors (in radians).
- Parameters:
- s1: numpy array
- The first vector.
- s2: numpy array
- The second vector.
- Returns: float
- The angle between vectors s1 and s2 in radians.
SID¶
-
pysptools.distance.
SID
(s1, s2)¶ Computes the spectral information divergence between two vectors.
- Parameters:
- s1: numpy array
- The first vector.
- s2: numpy array
- The second vector.
- Returns: float
- Spectral information divergence between s1 and s2.
- Reference
- C.-I. Chang, “An Information-Theoretic Approach to SpectralVariability, Similarity, and Discrimination for Hyperspectral Image” IEEE TRANSACTIONS ON INFORMATION THEORY, VOL. 46, NO. 5, AUGUST 2000.