Hi,

- 'band3' is not a typo. As said by Jonathan, band3 contains *NCC metric* values. By creating a mask of pixel with a correlation score higher than 0.9 you can select only good matches (NCC optimum is 1).

- Band1 contains *horizontal **disparities*. Checking pixel values means that you should check that the disparity values obtained on your scene are coherent with the search interval specified in the BlockMatching application. For instance: not setting the minimum horizontal disparity low enough can prevent the matches on features with a high elevation.

- Band2 *does *contain *vertical disparities* (which is obviously 0 everywhere). When doing the BlockMatching step, you have to specify a minimum and maximum vertical disparity for the exploration if you want to see vertical residues. By default, min and max vertical disparities are both set to 0 which imply no vertical exploration.

Regards,
Guillaume

Le 18/02/2014 17:37, Ofer Zilberstein a écrit :
Hi Jonathan,

Your answer confused me ...

    First - in the cookbook example  --  otbcli_BandMath -il
    disparity_map_ncc.tif  -out thres_hdisparity.tif uint8  -exp
    "if(im1b3>0.9,255,0)"  which mean that the h' disparity is in band
    3 ??? is it a typo error ?


Second - checking the pixel values the disparity image the values should not be between 0 -1 ?
          and finally - In my disparity image band 2 is empty ...

can you help me resolve this puzzle ?

Thanks in advanced

Ofer






On Monday, February 17, 2014 11:03:56 PM UTC+2, Jonathan Guinet wrote:

    Hi below my response about  Q1

    Band1 : Horizontal Disparity map
    Band2 : Vertical Disparity Map
    Band3: Metric values

    The BlockMatch output has 3 bands, the fourth is computed by
    Monteverdi and does not exist in input imagee

    cheers



    2014-02-17 17:33 GMT+01:00 Ofer Zilberstein <[email protected]
    <javascript:>>:


        Hi  OTB uses,

        I would like to share my experience and raise some Q' regard
        the process of extraction DSM from Pleiades Stereo Model

        This is my first step toward change detection between Pleiades
        fresh imagery & existing geo-data-base

        0) OS - Win 7 - 64bit

        1) I have Pleiades Regular Stereo Model

        2) I extracted ROI of 4000 x 4000 pixels for the left and then
        I created ROI with -mode.fit option for the right (according
        to best practice).

        3) I started with StereoFramework, and after it crashed I
        followed section 3.6  step by step and I successfully
        generated DSM file.

        4) Although there are some typo errors (e.g -
        in otbcli_StereoRectificationGridGenerator the -io.outimage1
        should be -io.outleft) the process went fine.

        *Q-1* - it is stated that otbcli_BlockMatching creates by
        default a two bands image : the horizontal and vertical
        disparities. When I look at  the image (e.g.
        disparity_map_ncc.tif) with Monteverdi I see 3 bends and
        amplitude.

                   bend 1 has values between -43 to 5
                   bend 2 is empty
                   bend 3 looks like disparity map with proper NCC
        values 0.5 to 0.98 (I think that this is the horizontal)
                   bend 4 (named amplitude) has values between 0 to 40

        In the step of filtering the NCC values (p. 81) , the example
        only shows how to filter horizontal (bend 3) then concatenate
        thresholded horizontal & vertical disparities...

        However - I cannot figure out where the vertical disparity
        resides ?

        ==================================

        *Q-2* - Is it correct' or essential for accurate DSM  and
        ortho' to follow chapter 3.2.5 Residual registration (between
        the two stereo images) before the DSM extraction ?

        Thanks in advanced ...

        Ofer

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