public interface CustomRankPrecision
Complete description of precision characteristics of rank operations, described in
interface. Usually this interface is used for instantiating
BasicRankMorphology.getInstance(net.algart.arrays.ArrayContext, double, net.algart.matrices.morphology.CustomRankPrecision) method.
This package offers
RankPrecision class, providing a ready set of instances of this interface,
enough for most situations. If you need another precision parameters, not listed in that class,
you can implement this interface yourself.
The classes, implementing this interface, are immutable and thread-safe: there are no ways to modify settings of the created instance.
|Modifier and Type||Field and Description|
The maximal possible number of analyzed bits: 30.
|Modifier and Type||Method and Description|
The bit levels.
Selects the histogram model used while calculating rank characteristics: true means the precise histogram model, false means the simple histogram model.
Returns the last element of the
static final int MAX_NUMBER_OF_ANALYZED_BITS
bitLevels()method, must not be greater than this value; in other case, an attempt to create an instance of
BasicRankMorphologywill lead to IllegalArgumentException.
The last element of this array bitLevels[bitLevels.length-1] is named
the number of analysed bits and specifies the logarithm of the length
of the histogram, used while calculating rank characteristics. More precisely, the length
of the histogram is
RankMorphology interface, section 3.
First bitLevels.length-1 elements of this array, i.e.
SummingHistogram.newSummingIntHistogram methods, when they are called for creating objects,
which really calculate the rank characteristics, described in
In other words, first bitLevels.length-1 elements describe the levels of the pyramid
of histograms: it is necessary for efficient processing large histograms,
consisting of thousands or millions bars.
This array must not be empty and must not contain more than 31 elements,
and all its elements must be sorted in strictly increasing order:
Below are possible examples of the array, returned by this method:
Note that the situation, when some or even all elements of this array are greater than 2β, is not an error — it just will lead to unjustified slowing down of calculations, because some levels of the pyramid of histograms will contain only 1 "wide" bar.
SummingHistogramclasses about these models.