initial sd-vbs

initial sd-vbs

add sd-vbs

sd-vbs

1 files changed, 33 insertions, 0 deletions

diff --git a/SD-VBS/benchmarks/sift/src/matlab/siftlocalmax.m b/SD-VBS/benchmarks/sift/src/matlab/siftlocalmax.m
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+% SIFTLOCALMAX  Find local maximizers
+%   SEL=SIFTLOCALMAX(F) returns the indexes of the local maximizers of
+%   the Q-dimensional array F.
+%
+%   A local maximizer is an element whose value is greater than the
+%   value of all its neighbors.  The neighbors of an element i1...iQ
+%   are the subscripts j1...jQ such that iq-1 <= jq <= iq (excluding
+%   i1...iQ itself).  For example, if Q=1 the neighbors of an element
+%   are its predecessor and successor in the linear order; if Q=2, its
+%   neighbors are the elements immediately to its north, south, west,
+%   est, north-west, north-est, south-west and south-est
+%   (8-neighborhood).
+%
+%   Points on the boundary of F are ignored (and never selected as
+%   local maximizers).
+%
+%   SEL=SIFTLOCALMAX(F,THRESH) accepts an element as a mazimizer only
+%   if it is at least THRES greater than all its neighbors.
+%
+%   SEL=SIFTLOCALMAX(F,THRESH,P) look for neighbors only in the first
+%   P dimensions of the Q-dimensional array F. This is useful to
+%   process F in ``slices''.
+%
+%   REMARK.  Matrices (2-array) with a singleton dimension are
+%   interpreted as vectors (1-array). So for example SIFTLOCALMAX([0 1
+%   0]) and SIFTLOCALMAX([0 1 0]') both return 2 as an aswer. However,
+%   if [0 1 0] is to be interpreted as a 1x2 matrix, then the correct
+%   answer is the empty set, as all elements are on the boundary.
+%   Unfortunately MATLAB does not distinguish between vectors and
+%   2-matrices with a singleton dimension.  To forece the
+%   interpretation of all matrices as 2-arrays, use
+%   SIFTLOCALMAX(F,TRESH,2) (but note that in this case the result is
+%   always empty!).