TBayerConversionMode Class Reference

Defines the Bayer conversion algorithm to use. More...

Static Public Attributes
static final int	bcmAdaptiveEdgeSensing = acquireJNI.bcmAdaptiveEdgeSensing_get()
	Adaptive edge sensing.
static final int	bcmAdaptiveEdgeSensingPlus = acquireJNI.bcmAdaptiveEdgeSensingPlus_get()
	Adaptive edge sensing plus.
static final int	bcmAdaptiveHomogeneityDirected = acquireJNI.bcmAdaptiveHomogeneityDirected_get()
	Adaptive edge sensing plus.
static final int	bcmAuto = acquireJNI.bcmAuto_get()
	Auto.
static final int	bcmLinearInterpolation = acquireJNI.bcmLinearInterpolation_get()
	Linear interpolation.
static final int	bcmLinearPacked = acquireJNI.bcmLinearPacked_get()
	Linear Packed.
static final int	bcmPacked = acquireJNI.bcmPacked_get()
	Packed.

Detailed Description

Defines the Bayer conversion algorithm to use.

Member Data Documentation

bcmAdaptiveEdgeSensing

final int bcmAdaptiveEdgeSensing = acquireJNI.bcmAdaptiveEdgeSensing_get()

static

Adaptive edge sensing.

This mode requires more CPU time than linear interpolation, but the resulting image more closely matches the original scene. Edges will be reconstructed with higher accuracy except for noisy images. For better results in noisy images mvIMPACT.acquire.TBayerConversionMode.bcmLinearInterpolation is the recommended mode.

bcmAdaptiveEdgeSensingPlus

final int bcmAdaptiveEdgeSensingPlus = acquireJNI.bcmAdaptiveEdgeSensingPlus_get()

static

Adaptive edge sensing plus.

This mode is even more demanding CPU-wise than adaptive edge sensing, but the resulting image is sharper and has fewer artifacts. The parameters of the sharpening filter can be set by the user, to fit specific needs.

Since

2.26.0

bcmAdaptiveHomogeneityDirected

final int bcmAdaptiveHomogeneityDirected = acquireJNI.bcmAdaptiveHomogeneityDirected_get()

static

Adaptive edge sensing plus.

This mode is most demanding CPU-wise, but the resulting image will have the best possible quality. It is based on the following algorithm: K. Hirakawa, T.W. Parks, Adaptive Homogeneity-Directed Demosaicing Algorithm, IEEE Trans. Image Processing, March, 2005.

Since

2.27.0

bcmAuto

final int bcmAuto = acquireJNI.bcmAuto_get()

static

Auto.

This mode automatically sets the Bayer conversion algorithm according to the format property of the camera description.

bcmLinearInterpolation

final int bcmLinearInterpolation = acquireJNI.bcmLinearInterpolation_get()

static

Linear interpolation.

This mode is fast but especially sharp edges will appear slightly blurred in the resulting image.

bcmLinearPacked

final int bcmLinearPacked = acquireJNI.bcmLinearPacked_get()

static

Linear Packed.

In this mode the resulting image will have half the height of the source image. The following algorithm will be used for generating the resulting image:

  1 2 3 4 ...   n
1 R G R G ... R G
2 G B G B ... G B
 
  | 1 | 2 | 3 | 4 | 5 |...| n |
1 |RGB|RGB|RGB|RGB|RGB|...|RGB|
2 |RGB|RGB|RGB|RGB|RGB|...|RGB|
 
R1(dest) = R11
G1(dest) = G21
B1(dest) = B22
R2(dest) = (R11 + R13) / 2
G2(dest) = G12
B2(dest) = B22
R3(dest) = R13
G3(dest) = G23
B3(dest) = (B22 + B24) / 2
...
Rn(dest) = R1(n-1)
Gn(dest) = G1(n)
Bn(dest) = B2(n)

This mode is mainly useful for line scan cameras as for area cameras this would modify the aspect ratio.

Since

2.5.9

bcmPacked

final int bcmPacked = acquireJNI.bcmPacked_get()

static

Packed.

In this mode the resulting image will have half the height of the source image. The following algorithm will be used for generating the resulting image:

  1 2 3 4 ...   n
1 R G R G ... R G
2 G B G B ... G B
 
  | 1 | 2 | 3 | 4 | 5 |...| n |
1 |RGB|RGB|RGB|RGB|RGB|...|RGB|
 
R1(dest) = R11
G1(dest) = (G12 + G21) / 2
B1(dest) = B22
R2(dest) = (R11 + R13) / 2
G2(dest) = ((G12 + G21) / 2) + (G12 + G23)) / 2
B2(dest) = (B22 + B24) / 2
...
Rn(dest) = R1(n-1)
Gn(dest) = (G1(n) + G2(n-1)) / 2
Bn(dest) = B2(n)

This mode is mainly useful for line scan cameras as for area cameras this would modify the aspect ratio.

Since

2.5.9