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Doubt about Interpreting PointCloud2 data

Hi, I am doing a research about sensor fusion, and I need to reconstruct a depth image, only with the contain of the topic: depth_registered/points. I already know that is a PointCloud2 type, and it has associated a PointField in order to interpret the data. I am following more or less this algorithm to get the Z coordinate it is also the same thing to get X, Y and RGB just moving the offsets, which are provide from the pointField information.
  1. Get the 9 , 10, 11 and 12 elements from the 32 elements matrix for each pixel

  2. Convert to binary each element (9,10,11,12)
  3. Concatenate the binary representations (for each elements).
  4. Invert all the concatenated representation (because is not a big endian)

  5. Convert the inverted representation in float32 value.

Well I have some results for my research and I am worried because making this algorithm I have some result for the Z matrix and the has to much noise (I think) I attached this result to show you my results.

 One of the restrictions of my research is that I am not able to use the switch between this topic and PCL (pcl_conversions ), I am just using a file which contains all the data (the data field for the PointCloud2 topic ) of the topic in each moment and working with it in Matlab.
I have attached the original image reconstruction (taking the 19, 18 and 17 for RGB ) from the 32 elements and the Z graphic for my Z result where each color represents an depth value .

Original Image, Z Matriz

Doubt about Interpreting PointCloud2 data

Hi, I am doing a research about sensor fusion, and I need to reconstruct a depth image, only with the contain of the topic: depth_registered/points. I already know that is a PointCloud2 type, and it has associated a PointField in order to interpret the data. I am following more or less this algorithm to get the Z coordinate it is also the same thing to get X, Y and RGB just moving the offsets, which are provide from the pointField information.
  1. Get the 9 , 10, 11 and 12 elements from the 32 elements matrix for each pixel

  2. Convert to binary each element (9,10,11,12)
  3. Concatenate the binary representations (for each elements).
  4. Invert all the concatenated representation (because is not a big endian)

  5. Convert the inverted representation in float32 value.

Well I have some results for my research and I am worried because making this algorithm I have some result for the Z matrix and the has to much noise (I think) I attached this result to show you my results.

 One of the restrictions of my research is that I am not able to use the switch between this topic and PCL (pcl_conversions ), I am just using a file which contains all the data (the data field for the PointCloud2 topic ) of the topic in each moment and working with it in Matlab.
I have attached the original image reconstruction (taking the 19, 18 and 17 for RGB ) from the 32 elements and the Z graphic for my Z result where each color represents an depth value .

Original Image, Z Matriz

Image Original Image

Z Matriz Z Matriz