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Fix for normalizeDoubleImage #92

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merged 7 commits into from
Apr 4, 2018
Merged

Fix for normalizeDoubleImage #92

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1938e66
Fixed normalizeFunction to really work
fox918 Mar 9, 2018
fe60d73
Fixed normalizeDoubleImageToRange because the real error was there...
fox918 Mar 9, 2018
db7154a
well, fixed my own mistake
fox918 Mar 9, 2018
10ba229
final fix
fox918 Mar 9, 2018
e0d411d
final fix of min == max
fox918 Mar 9, 2018
d30e122
Update PixelImageNormalization.scala
Andreas-Forster Apr 4, 2018
d58478c
Update PixelImageNormalization.scala
Andreas-Forster Apr 4, 2018
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16 changes: 9 additions & 7 deletions src/main/scala/scalismo/faces/image/PixelImageNormalization.scala
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Original file line number Diff line number Diff line change
Expand Up @@ -23,18 +23,20 @@ object PixelImageNormalization {

/** Normalizes the image such that its values are on the interval [lower, upper]. */
def normalizeDoubleImageToRange(image: PixelImage[Double], lower: Double, upper: Double): PixelImage[Double] = {
def normalizer(x: Double) = (x - lower) / (upper - lower)
if (lower < 0.0 || upper > 1.0)
image
else
require(lower < upper)
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The require can be removed as it does not change the correctness. Hence we could invert an image by: normalizeDoubleImageToRange(image,max,min)

val min = image.values.min
val max = image.values.max
if(min == max){ //if we would divide with 0
image.map(_ => (upper-lower)/2) //return mean of [lower,upper]
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Here it should be (lower+upper)/2 or lower+(upper-lower)/2. I would calculate the constant one above so that it is even better visible that the map does not depend on the position.

}else {
def normalizer(x: Double) = lower + (x - min) / (max - min) * (upper - lower)
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Can you precompute the normalization outside of the function? It might be more efficient except it is optimized by the compiler or the JVM and not much less readable I think.

image.map(normalizer)
}
}

/** Expands value range to the interval [0,1]. */
def normalizeDoubleImage(image: PixelImage[Double]): PixelImage[Double] = {
val min = image.values.min
val max = image.values.max
normalizeDoubleImageToRange(image, min, max)
normalizeDoubleImageToRange(image, 0.0, 1.0)
}

/** Normalize the image to range ([0,1], [0,1], [0,1]). (Each channel is normalized seperately.) */
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