boofcv.alg.feature.disparity.impl
Class UtilDisparityScore
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- boofcv.alg.feature.disparity.impl.UtilDisparityScore
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public class UtilDisparityScore extends java.lang.ObjectContains common functions for computing disparity scores.
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Constructor Summary
Constructors Constructor and Description UtilDisparityScore()
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Method Summary
All Methods Static Methods Concrete Methods Modifier and Type Method and Description static voidcomputeScoreRow(GrayF32 left, GrayF32 right, int row, float[] scores, int minDisparity, int maxDisparity, int regionWidth, float[] elementScore)Computes disparity score for an entire row.static voidcomputeScoreRow(GrayS16 left, GrayS16 right, int row, int[] scores, int minDisparity, int maxDisparity, int regionWidth, int[] elementScore)Computes disparity score for an entire row.static voidcomputeScoreRow(GrayU8 left, GrayU8 right, int row, int[] scores, int minDisparity, int maxDisparity, int regionWidth, int[] elementScore)Computes disparity score for an entire row.static voidcomputeScoreRowSad(GrayF32 left, GrayF32 right, int elementMax, int indexLeft, int indexRight, float[] elementScore)compute the score for each element all at once to encourage the JVM to optimize and encourage the JVM to optimize this section of code.static voidcomputeScoreRowSad(GrayS16 left, GrayS16 right, int elementMax, int indexLeft, int indexRight, int[] elementScore)compute the score for each element all at once to encourage the JVM to optimize and encourage the JVM to optimize this section of code.static voidcomputeScoreRowSad(GrayU8 left, GrayU8 right, int elementMax, int indexLeft, int indexRight, int[] elementScore)compute the score for each element all at once to encourage the JVM to optimize and encourage the JVM to optimize this section of code.
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Method Detail
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computeScoreRow
public static void computeScoreRow(GrayU8 left, GrayU8 right, int row, int[] scores, int minDisparity, int maxDisparity, int regionWidth, int[] elementScore)
Computes disparity score for an entire row. For a given disparity, the score for each region on the left share many components in common. Because of this the scores are computed with disparity being the outer most loop- Parameters:
left- left imageright- Right imagerow- Image row being examinedscores- Storage for disparity scores.minDisparity- Minimum disparity to considermaxDisparity- Maximum disparity to considerregionWidth- Size of the sample region's widthelementScore- Storage for scores of individual pixels
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computeScoreRowSad
public static void computeScoreRowSad(GrayU8 left, GrayU8 right, int elementMax, int indexLeft, int indexRight, int[] elementScore)
compute the score for each element all at once to encourage the JVM to optimize and encourage the JVM to optimize this section of code. Was original inline, but was actually slightly slower by about 3% consistently, It is in its own function so that it can be overridden and have different cost functions inserted easily.
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computeScoreRow
public static void computeScoreRow(GrayS16 left, GrayS16 right, int row, int[] scores, int minDisparity, int maxDisparity, int regionWidth, int[] elementScore)
Computes disparity score for an entire row. For a given disparity, the score for each region on the left share many components in common. Because of this the scores are computed with disparity being the outer most loop- Parameters:
left- left imageright- Right imagerow- Image row being examinedscores- Storage for disparity scores.minDisparity- Minimum disparity to considermaxDisparity- Maximum disparity to considerregionWidth- Size of the sample region's widthelementScore- Storage for scores of individual pixels
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computeScoreRowSad
public static void computeScoreRowSad(GrayS16 left, GrayS16 right, int elementMax, int indexLeft, int indexRight, int[] elementScore)
compute the score for each element all at once to encourage the JVM to optimize and encourage the JVM to optimize this section of code. Was original inline, but was actually slightly slower by about 3% consistently, It is in its own function so that it can be overridden and have different cost functions inserted easily.
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computeScoreRow
public static void computeScoreRow(GrayF32 left, GrayF32 right, int row, float[] scores, int minDisparity, int maxDisparity, int regionWidth, float[] elementScore)
Computes disparity score for an entire row. For a given disparity, the score for each region on the left share many components in common. Because of this the scores are computed with disparity being the outer most loop- Parameters:
left- left imageright- Right imagerow- Image row being examinedscores- Storage for disparity scores.minDisparity- Minimum disparity to considermaxDisparity- Maximum disparity to considerregionWidth- Size of the sample region's widthelementScore- Storage for scores of individual pixels
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computeScoreRowSad
public static void computeScoreRowSad(GrayF32 left, GrayF32 right, int elementMax, int indexLeft, int indexRight, float[] elementScore)
compute the score for each element all at once to encourage the JVM to optimize and encourage the JVM to optimize this section of code. Was original inline, but was actually slightly slower by about 3% consistently, It is in its own function so that it can be overridden and have different cost functions inserted easily.
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